WO2021166366A1 - Power conversion system, power conversion device, state estimation device, power conversion method, and power conversion program - Google Patents
Power conversion system, power conversion device, state estimation device, power conversion method, and power conversion program Download PDFInfo
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- WO2021166366A1 WO2021166366A1 PCT/JP2020/044906 JP2020044906W WO2021166366A1 WO 2021166366 A1 WO2021166366 A1 WO 2021166366A1 JP 2020044906 W JP2020044906 W JP 2020044906W WO 2021166366 A1 WO2021166366 A1 WO 2021166366A1
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02P—CONTROL OR REGULATION OF ELECTRIC MOTORS, ELECTRIC GENERATORS OR DYNAMO-ELECTRIC CONVERTERS; CONTROLLING TRANSFORMERS, REACTORS OR CHOKE COILS
- H02P29/00—Arrangements for regulating or controlling electric motors, appropriate for both AC and DC motors
- H02P29/02—Providing protection against overload without automatic interruption of supply
- H02P29/024—Detecting a fault condition, e.g. short circuit, locked rotor, open circuit or loss of load
Definitions
- One aspect of the disclosure relates to a power conversion system, a power conversion device, a state estimation device, a power conversion method, and a power conversion program.
- Patent Document 1 the torque command value from the inverter is compared with the torque judgment value, and when the torque command value deviates from the torque judgment value, it is determined that an abnormality has occurred in the drive force transmission mechanism including the drive belt or the drive chain.
- the control device to be used is described.
- the power conversion system includes a power conversion device that supplies power to the motor of the machine.
- the power conversion system produces a current distribution generator that generates current distribution information regarding the current distribution, which is a probability distribution of the frequency components of the current signal, based on the current signal indicating the current operation of the machine, and a past operation of the machine. It is provided with an estimation unit that estimates the current state of the machine based on the difference between the reference distribution information and the current distribution information regarding the reference distribution, which is a probability distribution based on the frequency component of the past signal shown.
- the power converter supplies power to the motor of the machine.
- the power conversion device generates current distribution information regarding the current distribution, which is a probability distribution of the frequency components of the current signal, based on the current signal indicating the current operation of the machine, and a current distribution generator that generates the past operation of the machine. It is provided with an estimation unit that estimates the current state of the machine based on the difference between the reference distribution information and the current distribution information regarding the reference distribution, which is a probability distribution based on the frequency component of the past signal shown.
- the state estimation device includes a current distribution generator that generates current distribution information regarding a current distribution, which is a probability distribution of frequency components of the current signal, based on a current signal indicating the current operation of the machine. It is provided with an estimation unit that estimates the current state of the machine based on the difference between the reference distribution information and the current distribution information regarding the reference distribution, which is a probability distribution based on the frequency component of the past signal indicating the past operation of the machine.
- the power conversion method is executed by a power conversion system having a power conversion device that supplies power to the motor of the machine.
- the power conversion method includes a step of generating current distribution information regarding a current distribution, which is a probability distribution of frequency components of the current signal, based on a current signal indicating the current operation of the machine, and a past signal indicating the past operation of the machine. It includes a step of estimating the current state of the machine based on the difference between the reference distribution information and the current distribution information regarding the reference distribution, which is a probability distribution based on the frequency component of.
- the power conversion program causes a computer system to function as a power conversion system having a power conversion device that supplies power to a machine motor.
- the power conversion program has a step of generating current distribution information regarding the current distribution, which is a probability distribution of the frequency component of the current signal, based on the current signal indicating the current operation of the machine, and a past signal indicating the past operation of the machine.
- the computer system is made to perform a step of estimating the current state of the machine based on the difference between the reference distribution information and the current distribution information regarding the reference distribution, which is a probability distribution based on the frequency component of.
- the state of the machine can be estimated appropriately.
- FIG. 1 is a diagram showing an example of application of the power conversion system 1 according to one aspect of the present disclosure.
- the electric power conversion system 1 is a control system that supplies electric power to the motor 91 of the machine 9.
- the power conversion system 1 is connected to one machine 9, but the power conversion system 1 may be connected to a plurality of machines 9.
- Machine 9 is a device that receives power to perform a predetermined operation according to a purpose and performs useful work.
- the machine 9 may be a robot or a machine tool.
- the machine 9 comprises a motor 91, a drive target 92, and a sensor 93.
- the motor 91 is a device that generates power for driving a drive target 92 that processes a work according to the electric power supplied from the power conversion system 1.
- the motor 91 may be a rotary motor that rotates the drive target 92, or may be a linear motor that displaces the drive target 92 along a straight line.
- the motor 91 may be a synchronous motor or an induction motor.
- the motor 91 may be a permanent magnet type synchronous motor such as an SPM (Surface Permanent Magnet) motor or an IPM (Interior Permanent Magnet) motor.
- the motor 91 may be a synchronous motor having no permanent magnet, such as a synchronous reluctance motor.
- the sensor 93 is a device that detects the response of the machine 9 operated by the electric power from the electric power conversion system 1.
- the response is the output of the machine to a command that is a command to control the machine.
- the response indicates information about at least one of the operation and state of the machine 9.
- the response may indicate information about at least one of the movements and states of the driven object 92, for example at least one of the position and speed of the driven object 92.
- the senor 93 is a rotary encoder that outputs a pulse signal having a frequency proportional to the operating speed of the drive target 92.
- the rotary encoder can acquire both the position and the speed of the drive target 92.
- the sensor 93 transmits a response signal indicating a response to the power conversion system 1.
- the power conversion system 1 further has a function of estimating the current state of the machine 9.
- the current state of the machine refers to the current state of the machine 9 itself or its components (eg, motor 91, drive target 92, or sensor 93).
- the current state may be represented by whether the machine 9 is normal or abnormal, or may be represented by the product life of the machine 9.
- the current state may be represented by the load applied to the machine 9, or may be represented by an abnormal factor of the machine 9.
- Product life is an index that indicates how long a machine will continue to operate normally.
- the load is the amount of power consumed by the machine (in other words, the amount of work).
- Anomalous factors are the causes of abnormalities in the machine.
- the current state may be represented by at least two combinations selected from normal / abnormal, product life, load, and abnormal factors.
- the power conversion system 1 includes a power conversion device 10 and a reference device 20 in order to supply power to the motor 91 and estimate the state of the machine 9.
- the power conversion device 10 is a device that supplies electric power to the motor 91.
- the power conversion device 10 generates electric power for operating the motor 91 based on an instruction from the host controller (for example, a command signal indicating a command) or an instruction input by the user, and uses the electric power. It is supplied to the motor 91.
- This supplied electric power corresponds to a driving force command such as a torque command and a current command.
- the power conversion device 10 may be, for example, a servo amplifier or an inverter.
- the power conversion device 10 may be incorporated in the machine 9.
- the power conversion device 10 also has a function of estimating the current state of the machine 9 operated by the electric power. Therefore, the power conversion device 10 also functions as a state estimation device according to the present disclosure.
- the reference device 20 is a device that transmits information used for estimating the current state of the machine 9 to the power conversion device 10.
- the above-mentioned host controller may also serve as the reference device 20. That is, in one example, the reference device 20 may be a host controller.
- FIG. 2 is a diagram showing an example of the hardware configuration of the computer 100 used in the power conversion system 1.
- the computer 100 includes a main body 110, a monitor 120, and an input device 130.
- the main body 110 is a device that executes the main functions of the computer.
- the main body 110 has a circuit 160, which has at least one processor 161, a memory 162, a storage 163, an input / output port 164, and a communication port 165.
- the storage 163 records a program for configuring each functional module of the main body 110.
- the storage 163 is a computer-readable recording medium such as a hard disk, a non-volatile semiconductor memory, a magnetic disk, or an optical disk.
- the memory 162 temporarily stores the program loaded from the storage 163, the calculation result of the processor 161 and the like.
- the processor 161 constitutes each functional module by executing a program in cooperation with the memory 162.
- the input / output port 164 inputs / outputs an electric signal to / from the monitor 120 or the input device 130 in response to a command from the processor 161.
- the input / output port 164 may input / output an electric signal to / from another device.
- the communication port 165 performs data communication with another device via the communication network N in accordance with a command from the processor 161.
- the monitor 120 is a device for displaying information output from the main body 110.
- the monitor 120 is a device capable of displaying graphics, such as a liquid crystal panel.
- the input device 130 is a device for inputting information to the main body 110.
- Examples of the input device 130 include operation interfaces such as a keypad, a mouse, and operation buttons.
- the monitor 120 and the input device 130 may be integrated as a touch panel.
- the main body 110, the monitor 120, and the input device 130 may be integrated.
- FIG. 3 is a diagram showing an example of the functional configuration of the power conversion system 1.
- the power conversion device 10 includes a control mode setting unit 11, a power conversion control unit 12, a current distribution generation unit 13, a reference distribution setting unit 14, and an estimation unit 15.
- the reference device 20 includes a reference distribution generation unit 21.
- the control mode setting unit 11 is a functional module for setting the control mode of the power conversion device 10.
- the control mode refers to a motor control method using a power converter.
- the number and type of control modes depends on the power converter 10 or the motor 91.
- the control mode of the inverter includes a V / F control mode and a vector control mode.
- the power converter 10 has a plurality of control modes corresponding to a plurality of types of machines 9.
- the control mode setting unit 11 sets at least one control mode from the plurality of control modes based on an instruction from the host controller or the user.
- the power conversion control unit 12 is a functional module that operates the power conversion device 10 in a predetermined pattern.
- the pattern refers to the type or type of operation of the power converter.
- the power conversion control unit 12 operates the power conversion device 10 in a pattern corresponding to at least one control mode set by the control mode setting unit 11.
- the current distribution generation unit 13 is a functional module that generates current distribution information regarding the current distribution, which is a probability distribution of the frequency component of the current signal, based on the current signal indicating the current operation of the machine 9.
- the current distribution is represented, for example, by the median (mean) and variance.
- the current signal is represented by the data in the most recent predetermined time width.
- the current signal may be a command signal obtained from the host controller, a control signal obtained in the power conversion device 10, or a response signal obtained from the sensor 93.
- the reference distribution setting unit 14 is a functional module that sets reference distribution information regarding a reference distribution, which is a probability distribution based on the frequency component of a past signal indicating the past operation of the machine 9. Like the current distribution, the reference distribution is represented by, for example, the median (mean) and variance.
- the past signal is a signal obtained before the current signal. Past signals are also represented by data in a predetermined time width. The past signal may be a command signal obtained from the host controller, a control signal obtained in the power conversion device 10, or a response signal obtained from the sensor 93.
- the reference distribution setting unit 14 includes a reference distribution storage unit 16, a reference distribution selection unit 17, and an adjustment unit 18.
- the reference distribution storage unit 16 is a functional module that stores reference distribution information, and stores, for example, a plurality of reference distribution information corresponding to a plurality of control modes.
- the reference distribution selection unit 17 is a functional module that selects reference distribution information corresponding to at least one control mode set by the control mode setting unit 11 from the reference distribution storage unit 16.
- the adjustment unit 18 is a functional module that adjusts the selected reference distribution information based on the information of the machine 9.
- the estimation unit 15 is a functional module that estimates the current state of the machine 9 based on the difference between the current distribution information and the reference distribution information.
- the reference distribution generation unit 21 is a functional module that generates reference distribution information based on past signals and current signals. In one example, the reference distribution generation unit 21 generates a plurality of reference distribution information corresponding to a plurality of control modes.
- the reference distribution generation unit 21 may generate individual reference distribution information based on the trained model. This trained model is generated based on past signals. For example, the reference distribution generation unit 21 executes machine learning using a set of signals (which corresponds to past signals) obtained by the trial run of the power conversion device 10 under the set control mode as input data. Generate a trained model corresponding to the control mode. When generating the trained model, the reference distribution generation unit 21 uses the signal (past signal) when the power conversion device 10 and the machine 9 normally operate as input data. The reference distribution generation unit 21 generates a trained model for each of the plurality of control modes. Therefore, the trained model is different for each control mode.
- Machine learning is a method of autonomously finding a law or rule by iteratively learning based on given information. Machine learning may be supervised learning or unsupervised learning such as reinforcement learning.
- the trained model is a calculation model that outputs reference distribution information when a signal indicating the operation of the machine 9 is input.
- the trained model is a computational model that is presumed to be optimal for outputting reference distribution information, and is not necessarily a “realistic optimal computational model”.
- the trained model may be constructed using a neural network. Considering that the past signal is time series data, the trained model may include a recurrent neural network (RNN). Alternatively, the trained model may include a convolutional neural network (CNN) that processes the frequency components of the signal indicating the operation of the machine.
- the reference distribution generation unit 21 executes a frequency analysis method such as a fast Fourier transform (FFT) on the signal to convert the signal into a frequency domain.
- FFT fast Fourier transform
- the reference distribution generation unit 21 inputs the individual frequency components obtained by the conversion to the CNN.
- the trained model may have a configuration that does not include a neural network.
- the reference distribution generation unit 21 includes a model database 22 and a model selection unit 23.
- the model database 22 is a functional module that stores at least one trained model that generates reference distribution information.
- the model database 22 stores a plurality of trained models corresponding to a plurality of control modes.
- the reference distribution generation unit 21 stores the individual trained models generated by the above method in the model database 22.
- the model selection unit 23 is a functional module that selects a trained model corresponding to at least one control mode set by the control mode setting unit 11 from the model database 22.
- the reference distribution generation unit 21 may set a threshold value to be used for estimating the current state based on the generation of the trained model.
- the reference distribution generation unit 21 may set a threshold value based on the standard deviation indicated by the reference distribution obtained by the trained model.
- the reference distribution generation unit 21 may set a multiple of the standard deviation ⁇ as a threshold value, for example, the threshold value may be set to ⁇ , 2 ⁇ , 3 ⁇ , or 4 ⁇ .
- the reference distribution generation unit 21 updates the reference distribution information in parallel with the estimation of the current state of the machine 9.
- the model selection unit 23 selects a trained model corresponding to at least one control mode set by the control mode setting unit 11 from the model database 22, and the reference distribution generation unit 21 is based on the trained model. Generate new reference distribution information.
- the reference distribution generation unit 21 inputs the current signal obtained by operating the power conversion device 10 in the control mode into the trained model to generate reference distribution information. That is, the reference distribution generation unit 21 may generate the reference distribution information based on the trained model that is generated based on the past signal and outputs the reference distribution information when the current signal is input.
- the reference distribution generation unit 21 calculates the frequency component of the current signal corresponding to the set control mode by a frequency analysis method such as FFT, inputs the frequency component to the selected trained model, and inputs the reference distribution information. To generate. That is, the reference distribution generation unit 21 generates reference distribution information based on a trained model that is generated based on the frequency component of the past signal and outputs the reference distribution information when the frequency component of the current signal is input. May be good.
- the reference distribution generation unit 21 may reset (update) the threshold value to be used for estimating the current state based on the update of the reference distribution information.
- the reference distribution generation unit 21 transmits the generated or updated reference distribution information to the power conversion device 10.
- the reference distribution setting unit 14 stores the reference distribution information in the reference distribution storage unit 16.
- the reference distribution information corresponding to the currently set control mode is registered or updated.
- the reference distribution generation unit 21 also transmits the threshold value to the power conversion device 10, and the reference distribution setting unit 14 stores the threshold value in the reference distribution storage unit 16. do. This process automatically registers or updates the threshold.
- FIG. 4 is a flowchart showing an example of the operation of the power conversion system 1 as a processing flow S1. That is, the power conversion system 1 executes the processing flow S1.
- step S11 the control mode setting unit 11 sets the control mode of the power conversion device 10.
- the control mode setting unit 11 sets at least one control mode from the plurality of control modes of the power conversion device 10 based on an instruction from the host controller or the user.
- step S12 the power conversion control unit 12 controls the power conversion device 10 based on the set control mode.
- the power conversion control unit 12 operates the power conversion device 10 in a pattern corresponding to the control mode.
- the power conversion device 10 supplies electric power to the motor 91 based on the pattern, and the motor 91 drives the drive target 92 according to the electric power.
- the power conversion system 1 estimates the current state of the machine 9 that operates by the processing.
- the reference distribution setting unit 14 sets the reference distribution information corresponding to the set control mode.
- the reference distribution selection unit 17 reads the reference distribution information corresponding to the control mode from the reference distribution storage unit 16.
- the adjusting unit 18 adjusts the reference distribution information based on the information of the machine 9.
- the information on the machine 9 may include, for example, at least one of a model number, serial number, operating status, and maintenance history.
- the operating status refers to information on the operation of the machine 9 or the surrounding environment of the machine 9. Examples of the operating status include the number of years of operation, the average load factor which is the average of the load factors applied to the machine 9 (for example, the motor 91) during operation, and the environmental temperature which is the temperature around the operating machine 9.
- the maintenance history is a record related to inspection or repair of the machine 9.
- the adjusting unit 18 may acquire the information of the machine 9 from a predetermined memory in the power conversion device 10 or the machine 9. As the adjustment of the reference distribution information, the adjusting unit 18 may change the median value (mean) of the reference distribution or the width (variance) of the reference distribution.
- the current distribution generation unit 13 acquires the current signal corresponding to the operation of the power conversion device 10 under the pattern corresponding to the set control mode.
- the power conversion control unit 12 acquires a signal in the latest predetermined time width from a device related to the power conversion system 1 such as a host controller, a power conversion device 10, and a sensor 93, and obtains a signal in the latest predetermined time width.
- the signal is output to the current distribution generation unit 13.
- the current distribution generation unit 13 acquires the signal as a current signal.
- the acquired current signal differs depending on the control mode.
- the current signal in V / F control mode can be at least one of a current signal and a voltage signal
- the current signal in vector control mode is a torque signal and a speed signal. Can be at least one of them. Since the current signal is information used to estimate the current state of the machine, it can be said to be a variable (state variable) for the estimation. Since the current signal corresponds to the control mode, it can be said that the control mode setting is a process corresponding to the switching of state variables.
- the current distribution generation unit 13 generates current distribution information based on the current signal.
- the current distribution generation unit 13 executes a frequency analysis method such as FFT on the current signal to convert the current signal into a frequency domain.
- the current distribution generation unit 13 executes a calculation based on the individual frequency components of the current signal obtained by the conversion, obtains the probability distribution of the frequency components of the current signal as the current distribution, and generates current distribution information regarding the current distribution. do.
- the current distribution generation unit 13 may execute Bayesian estimation based on the frequency component of the current signal to generate current distribution information.
- the current distribution generation unit 13 generates current distribution information by a calculation method having a lower calculation cost than the reference distribution generation unit 21. For example, when the reference distribution generation unit 21 generates a reference distribution by a trained model, Bayesian inference is a method having a lower calculation cost than the trained model.
- the estimation unit 15 estimates the current state of the machine 9 based on the current distribution information and the reference distribution information.
- the estimation unit 15 uses the reference distribution information when the power conversion device 10 is operated in a predetermined pattern. In one example, the estimation unit 15 uses the reference distribution information when the power conversion device 10 is operated in a pattern corresponding to the set control mode. Alternatively, the estimation unit 15 may use the reference distribution information adjusted by the adjustment unit 18. In any case, the estimation unit 15 calculates the difference between the current distribution information and the reference distribution information. For example, the estimation unit 15 calculates the Mahalanobis distance between the current distribution and the reference distribution as the difference. The Mahalanobis distance may be the distance between the median (mean) of the current distribution and the median (mean) of the reference distribution.
- the estimation unit 15 estimates the current state of the machine 9 based on the difference. For example, the estimation unit 15 expresses the current state of the machine 9 by using at least one of normal / abnormal, product life, load, and abnormal factor. The estimation unit 15 can output a detailed estimation result such as "the machine is normal but overloaded".
- the estimation unit 15 may compare the difference with a given threshold value to determine whether the machine 9 is normal or abnormal, and estimate the result of the determination as the current state of the machine 9. .. The estimation unit 15 determines that the machine 9 is normal when the difference is equal to or less than the threshold value, and determines that the machine 9 is abnormal when the difference exceeds the threshold value.
- the estimation unit 15 may determine the product life or load of the machine 9 based on the degree of deviation of the difference from the threshold value, and estimate the result of the determination as the current state of the machine 9.
- the degree of divergence is an index indicating how far the difference is from the threshold value, in other words, the distance between the difference and the threshold value.
- the estimation unit 15 determines that the smaller the degree of deviation, the longer the product life (or the lower the load).
- the estimation unit 15 may determine that the machine 9 is overloaded. If the difference exceeds the threshold value, it means that the machine 9 is abnormal. Therefore, the estimation unit 15 may determine that the product life is zero in that case.
- the estimation unit 15 may estimate the abnormal factor corresponding to the difference as the current state of the machine 9 based on the given relationship between the difference and the abnormal factor of the machine 9.
- the relationship between the difference and the anomalous factor may be expressed by a database.
- the estimation unit 15 refers to the database and extracts the anomalous factor corresponding to the difference.
- the database shows the correspondence between the order corresponding to the difference (an index indicating an integral multiple of the reference frequency based on the rotation speed of the motor 91) and the abnormal factor.
- the relationship between the difference and the anomalous factor may be represented by a trained model.
- This trained model is a calculation model that outputs anomalous factors when a difference is input, and is generated by machine learning using teacher data showing a large number of combinations of differences and anomalous factors, for example.
- the estimation unit 15 inputs a difference into the trained model and acquires an abnormal factor.
- the abnormality factor is set in consideration of various attributes such as the type of the machine 9 and the components of the machine 9. For example, an abnormality of the motor, an abnormality of the driving target, and the like can be mentioned as an example of the abnormality factor.
- Examples of abnormal factors related to the motor 91 which generally have a high occurrence rate, include deterioration of bearings, deterioration of insulation, burning, magnet peeling, and demagnetization.
- the threshold value used for estimating normal / abnormal, product life, or load may be set based on the generation of the trained model.
- the estimation unit 15 reads the threshold value from, for example, the reference distribution storage unit 16 and uses it.
- the estimation unit 15 outputs the estimation result.
- the estimation unit 15 may store the estimation result in a recording medium such as storage 163.
- the estimation unit 15 may display the estimation result on the monitor 120 in a format such as text, a moving image by computer graphics (CG), or a still image.
- CG computer graphics
- the power conversion system 1 may repeatedly execute the processes after step S14.
- the power conversion system 1 may repeatedly execute the processes after step S14 at a given interval while the machine 9 continues to operate.
- the current distribution generation unit 13 acquires a new current signal in step S14, and generates new current distribution information based on the current signal in step S15.
- the estimation unit 15 estimates the current state of the machine 9 based on the current distribution information and the reference distribution information, and outputs the estimation result in step S17.
- the reference distribution generation unit 21 may update the reference distribution information in parallel with the series of processes in steps S14 to S17. For example, the reference distribution generation unit 21 updates the reference distribution information using the current signal acquired in step S14, and also updates the threshold value if necessary. The updated reference distribution information (and updated thresholds, if any) will be used in subsequent estimates based on the new current signal. The reference distribution generation unit 21 updates the reference distribution information (and the threshold value) using the current signal only when the machine 9 is determined to be normal in the estimation based on the current signal acquired in step S14. You may.
- Each functional module of the power conversion system 1 is realized by loading a power conversion program on the processor 161 or the memory 162 and causing the processor 161 to execute the program.
- the power conversion program includes a code for realizing each functional module of the power conversion system 1.
- the processor 161 operates the input / output port 164 or the communication port 165 according to the power conversion program, and executes reading and writing of data in the memory 162 or the storage 163. By such processing, each functional module of the power conversion system 1 is realized.
- the power conversion program may be provided after being fixedly recorded on a non-temporary recording medium such as a CD-ROM, a DVD-ROM, or a semiconductor memory.
- the power conversion program may be provided via a communication network as a data signal superimposed on a carrier wave.
- the power conversion system includes a power conversion device that supplies power to the motor of the machine.
- the power conversion system produces a current distribution generator that generates current distribution information regarding the current distribution, which is a probability distribution of the frequency components of the current signal, based on the current signal indicating the current operation of the machine, and a past operation of the machine. It is provided with an estimation unit that estimates the current state of the machine based on the difference between the reference distribution information and the current distribution information regarding the reference distribution, which is a probability distribution based on the frequency component of the past signal shown.
- the power converter supplies power to the motor of the machine.
- the power conversion device generates current distribution information regarding the current distribution, which is a probability distribution of the frequency components of the current signal, based on the current signal indicating the current operation of the machine, and a current distribution generator that generates the past operation of the machine. It is provided with an estimation unit that estimates the current state of the machine based on the difference between the reference distribution information and the current distribution information regarding the reference distribution, which is a probability distribution based on the frequency component of the past signal shown.
- the state estimation device includes a current distribution generator that generates current distribution information regarding a current distribution, which is a probability distribution of frequency components of the current signal, based on a current signal indicating the current operation of the machine. It is provided with an estimation unit that estimates the current state of the machine based on the difference between the reference distribution information and the current distribution information regarding the reference distribution, which is a probability distribution based on the frequency component of the past signal indicating the past operation of the machine.
- the power conversion method is executed by a power conversion system having a power conversion device that supplies power to the motor of the machine.
- the power conversion method includes a step of generating current distribution information regarding a current distribution, which is a probability distribution of frequency components of the current signal, based on a current signal indicating the current operation of the machine, and a past signal indicating the past operation of the machine. It includes a step of estimating the current state of the machine based on the difference between the reference distribution information and the current distribution information regarding the reference distribution, which is a probability distribution based on the frequency component of.
- the power conversion program causes a computer system to function as a power conversion system having a power conversion device that supplies power to a machine motor.
- the power conversion program has a step of generating current distribution information regarding the current distribution, which is a probability distribution of the frequency component of the current signal, based on the current signal indicating the current operation of the machine, and a past signal indicating the past operation of the machine.
- the computer system is made to perform a step of estimating the current state of the machine based on the difference between the reference distribution information and the current distribution information regarding the reference distribution, which is a probability distribution based on the frequency component of.
- the current state of the machine is estimated based on the difference between the probability distribution indicating the current operation of the machine and the probability distribution based on the past operation of the machine.
- the probability distribution By using the probability distribution, the current state and the past state are compared with each other, including the certainty of estimation regarding the state of the machine, so that the current state of the machine can be estimated appropriately.
- the current state of a machine can be estimated without being affected by the characteristics of each machine. This estimation can improve the efficiency of work such as repairing machines and investigating the causes of machine abnormalities.
- the power conversion system may further include a power conversion control unit that operates the power conversion device in a predetermined pattern.
- the current distribution generation unit may generate current distribution information based on the current signal when the power conversion device is operated in a predetermined pattern, and the estimation unit operates the power conversion device in a predetermined pattern.
- the current state of the machine may be estimated based on the difference between the reference distribution information and the current distribution information. By comparing two probability distributions corresponding to the same pattern, the accuracy of estimation can be improved.
- the power conversion system corresponds to a control mode setting unit that sets at least one control mode from a plurality of control modes of the power conversion device corresponding to a plurality of types of machines, and at least one control mode.
- a reference distribution selection unit for selecting reference distribution information may be further provided.
- the estimator may estimate the current state of the machine based on the difference between the selected reference distribution information and the current distribution information. Since the reference distribution is prepared so as to correspond to each of the plurality of control modes of the power converter, the current state of the machine can be appropriately estimated according to the actual control mode of the power converter.
- the power conversion system may further include a storage unit that stores reference distribution information and an adjustment unit that adjusts reference distribution information based on machine information.
- the estimator may estimate the current state of the machine based on the difference between the adjusted reference distribution information and the current distribution information.
- the power conversion device may further include a storage unit that stores reference distribution information and an adjustment unit that adjusts reference distribution information based on machine information.
- the estimator may estimate the current state of the machine based on the difference between the adjusted reference distribution information and the current distribution information.
- a reference distribution that takes into account the characteristics of the machine is prepared, so the accuracy of estimation can be improved.
- the power conversion device may include a current distribution generation unit and an estimation unit.
- the power conversion system may further include a reference device that transmits reference distribution information to the power conversion device. Since the power converter performs the generation of current distribution information and the estimation of the current state of the machine, there is no need to introduce separate hardware resources for that estimation. Therefore, the power conversion system can be constructed inexpensively and easily.
- the power conversion system may further include a reference distribution generation unit that generates reference distribution information based on past signals and current signals.
- the reference distribution to be compared with the current distribution is generated considering not only the past signal but also the current signal. Therefore, the difference between the two probability distributions can be appropriately obtained, and the current state of the machine can be continuously estimated with high accuracy.
- the reference distribution generator generates the reference distribution information based on the trained model which is generated based on the past signal and outputs the reference distribution information when the current signal is input. You may. Since the accuracy of the reference distribution is improved by using the trained model, the current state of the machine can be estimated accurately.
- the reference distribution generator is generated based on the frequency component of the past signal, and is based on a trained model that outputs the reference distribution information when the frequency component of the current signal is input.
- Reference distribution information may be generated. By considering the frequency component of the current signal, reference distribution information that reflects the tendency of the change of the current signal is generated. The accuracy of estimation can be improved by using this reference distribution information.
- the power conversion system corresponds to a control mode setting unit that sets at least one control mode from a plurality of control modes of the power conversion device corresponding to a plurality of types of machines, and at least one control mode. It may further include a model selection unit that selects a trained model.
- the reference distribution generator may generate reference distribution information based on the selected trained model. Since the reference distribution information is generated using the trained model corresponding to the control mode of the power converter, the current state of the machine can be estimated accurately according to the actual control mode of the power converter.
- the estimator determines whether the machine is normal or abnormal based on the comparison of the difference with the threshold set based on the generation of the trained model.
- the result of the determination may be estimated as the current state of the machine. It can be said that the threshold value set based on the generation of the trained model is a reference value set objectively without depending on the human empirical rule. By using this threshold value, it is possible to objectively determine whether or not the machine is normal.
- the estimation unit determines the product life of the machine based on the degree of deviation of the difference from the threshold value set based on the generation of the trained model, and the result of the determination is the machine. It may be estimated as the current state of. It can be said that the threshold value set based on the generation of the trained model is a reference value set objectively without depending on the human empirical rule. By using this threshold value, the product life of the machine can be objectively determined.
- the current distribution generation unit may generate the current distribution information by a calculation method having a lower calculation cost than the reference distribution generation unit.
- the estimation unit may estimate the abnormal factor corresponding to the difference as the current state of the machine based on the given relationship between the difference and the abnormal factor of the machine. With this configuration, the cause of machine abnormality can be estimated in detail.
- the current distribution generator may execute Bayesian estimation based on the frequency component of the current signal to generate the current distribution information.
- Bayesian inference By using Bayesian inference, the current distribution can be obtained accurately even when the sample data is small.
- the probability distribution can be calculated on limited hardware resources.
- the accuracy of the calculation can be improved as the processing is repeated.
- the state estimation device may be applied to a device different from the power conversion device.
- the state estimation device may be applied to a configuration in which the state to be estimated appears at the frequency of the signal.
- the power conversion device described in the above embodiment is a device directly related to the current state of the machine from the viewpoint of supplying electric power to the motor of the machine. Therefore, by applying the state estimation device to the power conversion device, it is possible to accurately estimate the current state of the machine while saving the hardware resources in the power conversion system as a whole.
- the configuration of the power conversion system is not limited to the above embodiment.
- the reference device may reside in a computer system or control system separate from the power conversion system.
- the power conversion system and the other system are connected via a communication network, and the same functions and processes as those in the above embodiment are executed.
- the function of the reference device may be incorporated into the power conversion device or the state estimation device.
- the power conversion device 10 includes an adjusting unit 18, but this adjusting unit may be omitted. When there is only one control mode of the power converter, it is not necessary to separate the processing for each control mode.
- the hardware configuration of the system is not limited to the mode in which each functional module is realized by executing the program.
- the functional module in the above embodiment may be configured by a logic circuit specialized for the function, or may be configured by an ASIC (Application Specific Integrated Circuit) in which the logic circuit is integrated. ..
- the processing procedure of the method executed by at least one processor is not limited to the example in the above embodiment. For example, some of the steps (processes) described above may be omitted, or each step may be executed in a different order. In addition, any two or more steps of the above-mentioned steps may be combined, or a part of the steps may be modified or deleted. Alternatively, other steps may be performed in addition to each of the above steps.
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Abstract
Description
本開示の一側面は、電力変換システム、電力変換装置、状態推定装置、電力変換方法、および電力変換プログラムに関する。 One aspect of the disclosure relates to a power conversion system, a power conversion device, a state estimation device, a power conversion method, and a power conversion program.
特許文献1には、インバータからのトルク指令値とトルク判定値とを比較し、トルク指令値がトルク判定値から外れた場合、駆動ベルトまたは駆動チェーンを含む駆動力伝達機構に異常が生じたと判定する制御装置が記載されている。
In
機械の状態を適切に推定することが望まれている。 It is desired to properly estimate the state of the machine.
本開示の一側面に係る電力変換システムは、機械のモータに電力を供給する電力変換装置を有する。電力変換システムは、機械の現在の動作を示す現在信号に基づいて、該現在信号の周波数成分の確率分布であるカレント分布に関するカレント分布情報を生成するカレント分布生成部と、機械の過去の動作を示す過去信号の周波数成分に基づく確率分布であるリファレンス分布に関するリファレンス分布情報とカレント分布情報との差異に基づいて、機械の現在状態を推定する推定部とを備える。 The power conversion system according to one aspect of the present disclosure includes a power conversion device that supplies power to the motor of the machine. The power conversion system produces a current distribution generator that generates current distribution information regarding the current distribution, which is a probability distribution of the frequency components of the current signal, based on the current signal indicating the current operation of the machine, and a past operation of the machine. It is provided with an estimation unit that estimates the current state of the machine based on the difference between the reference distribution information and the current distribution information regarding the reference distribution, which is a probability distribution based on the frequency component of the past signal shown.
本開示の一側面に係る電力変換装置は、機械のモータに電力を供給する。電力変換装置は、機械の現在の動作を示す現在信号に基づいて、該現在信号の周波数成分の確率分布であるカレント分布に関するカレント分布情報を生成するカレント分布生成部と、機械の過去の動作を示す過去信号の周波数成分に基づく確率分布であるリファレンス分布に関するリファレンス分布情報とカレント分布情報との差異に基づいて、機械の現在状態を推定する推定部とを備える。 The power converter according to one aspect of the present disclosure supplies power to the motor of the machine. The power conversion device generates current distribution information regarding the current distribution, which is a probability distribution of the frequency components of the current signal, based on the current signal indicating the current operation of the machine, and a current distribution generator that generates the past operation of the machine. It is provided with an estimation unit that estimates the current state of the machine based on the difference between the reference distribution information and the current distribution information regarding the reference distribution, which is a probability distribution based on the frequency component of the past signal shown.
本開示の一側面に係る状態推定装置は、機械の現在の動作を示す現在信号に基づいて、該現在信号の周波数成分の確率分布であるカレント分布に関するカレント分布情報を生成するカレント分布生成部と、機械の過去の動作を示す過去信号の周波数成分に基づく確率分布であるリファレンス分布に関するリファレンス分布情報とカレント分布情報との差異に基づいて、機械の現在状態を推定する推定部とを備える。 The state estimation device according to one aspect of the present disclosure includes a current distribution generator that generates current distribution information regarding a current distribution, which is a probability distribution of frequency components of the current signal, based on a current signal indicating the current operation of the machine. It is provided with an estimation unit that estimates the current state of the machine based on the difference between the reference distribution information and the current distribution information regarding the reference distribution, which is a probability distribution based on the frequency component of the past signal indicating the past operation of the machine.
本開示の一側面に係る電力変換方法は、機械のモータに電力を供給する電力変換装置を有する電力変換システムにより実行される。電力変換方法は、機械の現在の動作を示す現在信号に基づいて、該現在信号の周波数成分の確率分布であるカレント分布に関するカレント分布情報を生成するステップと、機械の過去の動作を示す過去信号の周波数成分に基づく確率分布であるリファレンス分布に関するリファレンス分布情報とカレント分布情報との差異に基づいて、機械の現在状態を推定するステップとを含む。 The power conversion method according to one aspect of the present disclosure is executed by a power conversion system having a power conversion device that supplies power to the motor of the machine. The power conversion method includes a step of generating current distribution information regarding a current distribution, which is a probability distribution of frequency components of the current signal, based on a current signal indicating the current operation of the machine, and a past signal indicating the past operation of the machine. It includes a step of estimating the current state of the machine based on the difference between the reference distribution information and the current distribution information regarding the reference distribution, which is a probability distribution based on the frequency component of.
本開示の一側面に係る電力変換プログラムは、機械のモータに電力を供給する電力変換装置を有する電力変換システムとしてコンピュータシステムを機能させる。電力変換プログラムは、機械の現在の動作を示す現在信号に基づいて、該現在信号の周波数成分の確率分布であるカレント分布に関するカレント分布情報を生成するステップと、機械の過去の動作を示す過去信号の周波数成分に基づく確率分布であるリファレンス分布に関するリファレンス分布情報とカレント分布情報との差異に基づいて、機械の現在状態を推定するステップとをコンピュータシステムに実行させる。 The power conversion program according to one aspect of the present disclosure causes a computer system to function as a power conversion system having a power conversion device that supplies power to a machine motor. The power conversion program has a step of generating current distribution information regarding the current distribution, which is a probability distribution of the frequency component of the current signal, based on the current signal indicating the current operation of the machine, and a past signal indicating the past operation of the machine. The computer system is made to perform a step of estimating the current state of the machine based on the difference between the reference distribution information and the current distribution information regarding the reference distribution, which is a probability distribution based on the frequency component of.
本開示の一側面によれば、機械の状態を適切に推定できる。 According to one aspect of the present disclosure, the state of the machine can be estimated appropriately.
以下、添付図面を参照しながら本開示での実施形態を詳細に説明する。図面の説明において同一または同等の要素には同一の符号を付し、重複する説明を省略する。 Hereinafter, embodiments in the present disclosure will be described in detail with reference to the accompanying drawings. In the description of the drawings, the same or equivalent elements are designated by the same reference numerals, and duplicate description is omitted.
[システムの構成]
図1は本開示の一側面に係る電力変換システム1の適用の一例を示す図である。電力変換システム1は機械9のモータ91に電力を供給する制御システムである。図1の例では電力変換システム1が一つの機械9に接続するが、電力変換システム1は複数の機械9と接続してもよい。
[System configuration]
FIG. 1 is a diagram showing an example of application of the
機械9は、動力を受けて目的に応じた所定の動作を行って、有用な仕事を実行する装置である。例えば、機械9はロボットでもよいし工作機械でもよい。一例では、機械9はモータ91、駆動対象92、およびセンサ93を備える。
モータ91は、電力変換システム1から供給される電力に応じて、ワークを処理する駆動対象92を駆動させるための動力を発生させる装置である。モータ91は、駆動対象92を回転させる回転型モータであってもよいし、駆動対象92を直線に沿って変位させるリニア型モータであってもよい。モータ91は、同期電動機であってもよいし、誘導電動機であってもよい。モータ91は、SPM(Surface Permanent Magnet)モータ、IPM(Interior Permanent Magnet)モータ等の永久磁石型の同期電動機であってもよい。モータ91は、シンクロナスリラクタンスモータ(synchronous reluctance motor)のような、永久磁石を有しない同期電動機であってもよい。
The
センサ93は、電力変換システム1からの電力によって動作する機械9の応答を検出する装置である。応答とは、機械を制御するための命令である指令に対する該機械の出力をいう。例えば、応答は機械9の動作および状態の少なくとも一方に関する情報を示す。応答は駆動対象92の動作および状態の少なくとも一方に関する情報を示してもよく、例えば駆動対象92の位置および速度の少なくとも一方を示してもよい。モータ91が回転型である場合には、モータ91による駆動対象92の回転角度が「位置」に相当し、モータ91による駆動対象92の回転速度が「速度」に相当する。一例では、センサ93は駆動対象92の動作速度に比例した周波数のパルス信号を出力するロータリーエンコーダである。ロータリーエンコーダは駆動対象92の位置および速度の両方を取得できる。センサ93は応答を示す応答信号を電力変換システム1に送信する。
The
電力変換システム1は、機械9の現在状態を推定する機能をさらに有する。本開示において、機械の現在状態とは、機械9そのものまたは機械9の構成要素(例えばモータ91、駆動対象92、またはセンサ93)の現在の状況をいう。現在状態は、機械9が正常であるか異常であるかによって表されてもよいし、機械9の製品寿命によって表されてもよい。あるいは、現在状態は機械9に掛かっている負荷によって表されてもよいし、機械9の異常要因によって表されてもよい。製品寿命とは機械があとどのくらい長く正常に動作し続けるかを示す指数である。負荷とは機械により消費される動力の量(言い換えると仕事量)をいう。異常要因とは機械が異常になった原因をいう。現在状態は、正常/異常、製品寿命、負荷、および異常要因から選択される少なくとも二つの組合せによって表されてもよい。
The
モータ91への電力供給と機械9の状態の推定とを実行するために、一例では電力変換システム1は電力変換装置10およびリファレンス装置20を備える。電力変換装置10は電力をモータ91に供給する装置である。電力変換装置10は、上位コントローラ(ホストコントローラ)からの指示(例えば、指令を示す指令信号)、またはユーザにより入力された指示に基づいて、モータ91を動かすための電力を生成し、その電力をモータ91に供給する。この供給される電力は、トルク指令、電流指令などのような駆動力指令に相当する。電力変換装置10は例えば、サーボアンプであってもよいし、インバータであってもよい。電力変換装置10は機械9内に組み込まれてもよい。電力変換装置10は、その電力によって動作する機械9の現在状態を推定する機能も有する。したがって、電力変換装置10は本開示に係る状態推定装置としても機能する。リファレンス装置20は機械9の現在状態を推定するために用いられる情報を電力変換装置10に送信する装置である。上記の上位コントローラ(ホストコントローラ)がリファレンス装置20の役割を兼ねてもよい。すなわち、一例では、リファレンス装置20は上位コントローラ(ホストコントローラ)であってもよい。
In one example, the
図2は、電力変換システム1で用いられるコンピュータ100のハードウェア構成の一例を示す図である。この例では、コンピュータ100は本体110、モニタ120、および入力デバイス130を備える。
FIG. 2 is a diagram showing an example of the hardware configuration of the
本体110はコンピュータの主たる機能を実行する装置である。本体110は回路160を有し、回路160は、少なくとも一つのプロセッサ161と、メモリ162と、ストレージ163と、入出力ポート164と、通信ポート165とを有する。ストレージ163は、本体110の各機能モジュールを構成するためのプログラムを記録する。ストレージ163は、ハードディスク、不揮発性の半導体メモリ、磁気ディスク、光ディスク等の、コンピュータ読み取り可能な記録媒体である。メモリ162は、ストレージ163からロードされたプログラム、プロセッサ161の演算結果等を一時的に記憶する。プロセッサ161は、メモリ162と協働してプログラムを実行することで、各機能モジュールを構成する。入出力ポート164は、プロセッサ161からの指令に応じて、モニタ120または入力デバイス130との間で電気信号の入出力を行う。入出力ポート164は他の装置との間で電気信号の入出力を行ってもよい。通信ポート165は、プロセッサ161からの指令に従って、通信ネットワークNを介して他の装置との間でデータ通信を行う。
The
モニタ120は、本体110から出力された情報を表示するための装置である。例えばモニタ120は、液晶パネルのような、グラフィック表示が可能な装置である。
The
入力デバイス130は、本体110に情報を入力するための装置である。入力デバイス130の例としてキーパッド、マウス、操作ボタン等の操作インタフェースが挙げられる。
The
モニタ120および入力デバイス130はタッチパネルとして一体化されていてもよい。例えばタブレットコンピュータのように、本体110、モニタ120、および入力デバイス130が一体化されていてもよい。
The
図3は電力変換システム1の機能構成の一例を示す図である。一例では、電力変換装置10は制御モード設定部11、電力変換制御部12、カレント分布生成部13、リファレンス分布設定部14、および推定部15を備える。リファレンス装置20はリファレンス分布生成部21を備える。
FIG. 3 is a diagram showing an example of the functional configuration of the
制御モード設定部11は電力変換装置10の制御モードを設定する機能モジュールである。制御モードとは電力変換装置によるモータの制御方式をいう。制御モードの個数および種類は電力変換装置10またはモータ91に依存する。例えば、一般にインバータの制御モードとしてV/F制御モードおよびベクトル制御モードが挙げられる。一例では、電力変換装置10は機械9の複数の種類に対応する複数の制御モードを有する。制御モード設定部11は上位コントローラ(ホストコントローラ)またはユーザからの指示に基づいてその複数の制御モードから少なくとも一つの制御モードを設定する。
The control
電力変換制御部12は所定のパターンで電力変換装置10を動作させる機能モジュールである。パターンとは電力変換装置の動作の型または種類をいう。一例では、電力変換制御部12は制御モード設定部11によって設定された少なくとも一つの制御モードに対応するパターンで電力変換装置10を動作させる。
The power
カレント分布生成部13は、機械9の現在の動作を示す現在信号に基づいて、該現在信号の周波数成分の確率分布であるカレント分布に関するカレント分布情報を生成する機能モジュールである。カレント分布は例えば中央値(平均)および分散によって表される。現在信号は直近の所定の時間幅におけるデータによって表される。現在信号は、上位コントローラ(ホストコントローラ)から得られる指令信号でもよいし、電力変換装置10内で得られる制御信号でもよいし、センサ93から得られる応答信号でもよい。
The current
リファレンス分布設定部14は、機械9の過去の動作を示す過去信号の周波数成分に基づく確率分布であるリファレンス分布に関するリファレンス分布情報を設定する機能モジュールである。カレント分布と同様に、リファレンス分布も例えば中央値(平均)および分散によって表される。過去信号とは現在信号よりも前に得られる信号をいう。過去信号も所定の時間幅におけるデータによって表される。過去信号も、上位コントローラ(ホストコントローラ)から得られる指令信号でもよいし、電力変換装置10内で得られる制御信号でもよいし、センサ93から得られる応答信号でもよい。
The reference
リファレンス分布設定部14はリファレンス分布記憶部16、リファレンス分布選択部17、および調整部18を備える。リファレンス分布記憶部16はリファレンス分布情報を記憶する機能モジュールであり、例えば、複数の制御モードに対応する複数のリファレンス分布情報を記憶する。リファレンス分布選択部17は、制御モード設定部11によって設定された少なくとも一つの制御モードに対応するリファレンス分布情報をリファレンス分布記憶部16から選択する機能モジュールである。調整部18は選択されたリファレンス分布情報を機械9の情報に基づいて調整する機能モジュールである。
The reference
推定部15はカレント分布情報とリファレンス分布情報との差異に基づいて機械9の現在状態を推定する機能モジュールである。
The
リファレンス分布生成部21は過去信号および現在信号に基づいてリファレンス分布情報を生成する機能モジュールである。一例では、リファレンス分布生成部21は複数の制御モードに対応して複数のリファレンス分布情報を生成する。
The reference
リファレンス分布生成部21は学習済みモデルに基づいて個々のリファレンス分布情報を生成してもよい。この学習済みモデルは過去信号に基づいて生成される。例えば、リファレンス分布生成部21は、設定された制御モード下での電力変換装置10の試運転によって得られた信号(これが過去信号に相当する)の集合を入力データとして用いる機械学習を実行して、その制御モードに対応する学習済みモデルを生成する。学習済みモデルを生成する際には、リファレンス分布生成部21は電力変換装置10および機械9が正常に動作した際の信号(過去信号)を入力データとして用いる。リファレンス分布生成部21は複数の制御モードのそれぞれについて学習済みモデルを生成する。したがって、学習済みモデルは制御モード毎に異なる。機械学習とは、与えられた情報に基づいて反復的に学習することで、法則またはルールを自律的に見つけ出す手法をいう。機械学習は教師あり学習でもよいし、強化学習などの教師なし学習でもよい。
The reference
学習済みモデルは、機械9の動作を示す信号が入力されるとリファレンス分布情報を出力する計算モデルである。学習済みモデルはリファレンス分布情報を出力するために最適であると推定される計算モデルであって、“現実に最適である計算モデル”とは限らないことに留意されたい。学習済みモデルはニューラルネットワークを用いて構築されてもよい。過去信号が時系列データであることを考慮して、学習済みモデルは再帰型ニューラルネットワーク(RNN)を含んでもよい。あるいは、学習済みモデルは、機械の動作を示す信号の周波数成分を処理する畳み込みニューラルネットワーク(CNN)を含んでもよい。この場合、リファレンス分布生成部21はその信号に対して高速フーリエ変換(FFT)などの周波数解析手法を実行して該信号を周波数領域に変換する。リファレンス分布生成部21はその変換によって得られた個々の周波数成分をCNNに入力する。さらに別の例として、学習済みモデルはニューラルネットワークを含まない構成を有してもよい。
The trained model is a calculation model that outputs reference distribution information when a signal indicating the operation of the
リファレンス分布生成部21はモデルデータベース22およびモデル選択部23を備える。モデルデータベース22は、リファレンス分布情報を生成する少なくとも一つの学習済みモデルを記憶する機能モジュールである。例えば、モデルデータベース22は複数の制御モードに対応する複数の学習済みモデルを記憶する。リファレンス分布生成部21は上記の手法によって生成された個々の学習済みモデルをモデルデータベース22に格納する。モデル選択部23は、制御モード設定部11によって設定された少なくとも一つの制御モードに対応する学習済みモデルをモデルデータベース22から選択する機能モジュールである。
The reference
リファレンス分布生成部21は学習済みモデルの生成に基づいて、現在状態の推定に用いるための閾値を設定してもよい。一例として、リファレンス分布生成部21は、その学習済みモデルによって得られるリファレンス分布で示される標準偏差に基づいて閾値を設定してもよい。例えば、リファレンス分布生成部21は標準偏差σの倍数を閾値として設定してもよく、例えば閾値をσ、2σ、3σ、または4σに設定してもよい。
The reference
一例では、リファレンス分布生成部21は機械9の現在状態の推定と並行してリファレンス分布情報を更新する。この場合、モデル選択部23が、制御モード設定部11によって設定された少なくとも一つの制御モードに対応する学習済みモデルをモデルデータベース22から選択し、リファレンス分布生成部21がその学習済みモデルに基づいて新たなリファレンス分布情報を生成する。一例では、リファレンス分布生成部21は、その制御モードで電力変換装置10を動作させることで得られた現在信号をその学習済みモデルに入力して、リファレンス分布情報を生成する。すなわち、リファレンス分布生成部21は、過去信号に基づいて生成され、現在信号が入力されるとリファレンス分布情報を出力する学習済みモデルに基づいて、リファレンス分布情報を生成してもよい。あるいは、リファレンス分布生成部21は、設定された制御モードに対応する現在信号の周波数成分をFFTなどの周波数解析手法によって算出し、選択された学習済みモデルにその周波数成分を入力してリファレンス分布情報を生成する。すなわち、リファレンス分布生成部21は、過去信号の周波数成分に基づいて生成され、現在信号の周波数成分が入力されるとリファレンス分布情報を出力する学習済みモデルに基づいて、リファレンス分布情報を生成してもよい。リファレンス分布生成部21はリファレンス分布情報の更新に基づいて、現在状態の推定に用いるための閾値を再設定(更新)してもよい。
In one example, the reference
リファレンス分布生成部21は生成または更新されたリファレンス分布情報を電力変換装置10に送信する。電力変換装置10ではリファレンス分布設定部14がそのリファレンス分布情報をリファレンス分布記憶部16に格納する。この結果、現在設定されている制御モードに対応するリファレンス分布情報が登録または更新される。現在状態の推定に用いるための閾値が設定された場合には、リファレンス分布生成部21はその閾値も電力変換装置10に送信し、リファレンス分布設定部14はその閾値をリファレンス分布記憶部16に格納する。この処理によりその閾値が自動的に登録または更新される。
The reference
[電力変換方法]
本開示に係る電力変換方法の一例として、図4を参照しながら、電力変換システム1により実行される処理手順の一例を説明する。図4は電力変換システム1の動作の一例を処理フローS1として示すフローチャートである。すなわち、電力変換システム1は処理フローS1を実行する。
[Power conversion method]
As an example of the power conversion method according to the present disclosure, an example of a processing procedure executed by the
ステップS11では、制御モード設定部11が電力変換装置10の制御モードを設定する。一例では、制御モード設定部11は上位コントローラ(ホストコントローラ)またはユーザからの指示に基づいて電力変換装置10の複数の制御モードから少なくとも一つの制御モードを設定する。
In step S11, the control
ステップS12では、電力変換制御部12が設定された制御モードに基づいて電力変換装置10を制御する。電力変換制御部12はその制御モードに対応するパターンで電力変換装置10を動作させる。電力変換装置10はそのパターンに基づいてモータ91に電力を供給し、モータ91がその電力に応じて駆動対象92を駆動させる。電力変換システム1はその処理によって動作する機械9の現在状態を推定する。
In step S12, the power
ステップS13では、リファレンス分布設定部14が、設定された制御モードに対応するリファレンス分布情報を設定する。リファレンス分布設定部14では、リファレンス分布選択部17がその制御モードに対応するリファレンス分布情報をリファレンス分布記憶部16から読み出す。そして、調整部18がそのリファレンス分布情報を機械9の情報に基づいて調整する。機械9の情報は例えば、型番、シリアル番号、稼働状況、およびメンテナンス履歴のうちの少なくとも一つを含んでよい。稼働状況とは、機械9の稼働または機械9の周辺環境に関する情報をいう。稼働状況の例として、稼働年数と、稼働時に機械9(例えばモータ91)に掛かる負荷率の平均である平均負荷率と、稼働する機械9の周辺の温度である環境温度とが挙げられる。メンテナンス履歴とは機械9の点検または修理に関する記録をいう。調整部18は機械9の情報を電力変換装置10内の所定のメモリまたは機械9から取得してよい。リファレンス分布情報の調整として、調整部18はリファレンス分布の中央値(平均)を変更してもよいし、リファレンス分布の幅(分散)を変更してもよい。
In step S13, the reference
ステップS14では、カレント分布生成部13が、設定された制御モードに対応するパターン下での電力変換装置10の稼働に対応する現在信号を取得する。一例では、電力変換制御部12が上位コントローラ(ホストコントローラ)、電力変換装置10、センサ93などのような電力変換システム1に関連する装置から直近の所定の時間幅における信号を取得して、この信号をカレント分布生成部13に出力する。カレント分布生成部13はその信号を現在信号として取得する。取得される現在信号は制御モードに応じて異なる。例えば、電力変換装置10がインバータである場合には、V/F制御モードでの現在信号は電流信号および電圧信号の少なくとも一方であり得るし、ベクトル制御モードでの現在信号はトルク信号および速度信号の少なくとも一方であり得る。現在信号は機械の現在状態を推定するために用いられる情報なので、その推定のための変数(状態変数)であるといえる。その現在信号は制御モードに対応するので、制御モードの設定は状態変数の切り替えに相当する処理であるといえる。
In step S14, the current
ステップS15では、カレント分布生成部13がその現在信号に基づいてカレント分布情報を生成する。一例では、カレント分布生成部13はその現在信号に対してFFTなどの周波数解析手法を実行して現在信号を周波数領域に変換する。カレント分布生成部13はその変換によって得られた現在信号の個々の周波数成分に基づく計算を実行して、現在信号の周波数成分の確率分布をカレント分布として求め、そのカレント分布に関するカレント分布情報を生成する。例えば、カレント分布生成部13は現在信号の周波数成分に基づくベイズ推定を実行してカレント分布情報を生成してもよい。一例では、カレント分布生成部13はリファレンス分布生成部21よりも計算コストが少ない計算方法によってカレント分布情報を生成する。例えば、リファレンス分布生成部21が学習済みモデルによってリファレンス分布を生成する場合に、ベイズ推定はその学習済みモデルよりも計算コストが少ない方法である。
In step S15, the current
ステップS16では、推定部15がカレント分布情報およびリファレンス分布情報に基づいて機械9の現在状態を推定する。推定部15は所定のパターンで電力変換装置10を動作させた際のリファレンス分布情報を用いる。一例では、推定部15は設定された制御モードに対応するパターンで電力変換装置10を動作させた際のリファレンス分布情報を用いる。あるいは、推定部15は調整部18によって調整されたリファレンス分布情報を用いてもよい。いずれにしても、推定部15はカレント分布情報とリファレンス分布情報との差異を算出する。例えば、推定部15はカレント分布とリファレンス分布との間のマハラノビス距離をその差異として算出する。そのマハラノビス距離は、カレント分布の中央値(平均)とリファレンス分布の中央値(平均)との距離でもよい。続いて、推定部15はその差異に基づいて機械9の現在状態を推定する。例えば推定部15は、正常/異常、製品寿命、負荷、および異常要因のうちの少なくとも一つを用いてその機械9の現在状態を表現する。推定部15は、例えば「機械は正常であるが過負荷である」などのような詳細な推定結果を出力し得る。
In step S16, the
一例として、推定部15はその差異を所与の閾値と比較して、機械9が正常であるか異常であるかを判定し、その判定の結果を機械9の現在状態として推定してもよい。推定部15は差異がその閾値以下である場合には機械9が正常であると判定し、差異がその閾値を超える場合には機械9が異常であると判定する。
As an example, the
別の例として、推定部15はその閾値からの差異の乖離度に基づいて機械9の製品寿命または負荷を判定し、その判定の結果を機械9の現在状態として推定してもよい。乖離度とは差異が閾値からどのくらい離れているかを示す指数であり、言い換えると、差異と閾値との間の距離である。一例では、差異が閾値以下である場合において、推定部15は乖離度が小さいほど製品寿命を長く(または負荷を低く)判定する。差異が閾値以下であるが乖離度が大きい場合には、推定部15は機械9が過負荷であると判定してもよい。差異が閾値を超えるということは機械9が異常であることを意味するので、推定部15はその場合に製品寿命がゼロであると判定してもよい。
As another example, the
さらに別の例として、推定部15は、差異と機械9の異常要因との所与の関係に基づいて、差異に対応する異常要因を機械9の現在状態として推定してもよい。差異と異常要因との関係はデータベースによって表現されてもよく、この場合には、推定部15はそのデータベースを参照して、差異に対応する異常要因を抽出する。例えば、そのデータベースは、差異に対応する次数(モータ91の回転数に基づく基準周波数の整数倍を示す指数)と異常要因との対応関係を示す。あるいは、差異と異常要因との関係は学習済みモデルによって表現されてもよい。この学習済みモデルは、差異が入力されると異常要因を出力する計算モデルであり、例えば、差異および異常要因の多数の組合せを示す教師データを用いた機械学習によって生成される。推定部15はその学習済みモデルに差異を入力して異常要因を取得する。異常要因は機械9の種類、機械9の構成要素などの様々な属性を考慮して設定される。例えば、異常要因の例としてモータの異常、駆動対象の異常などが挙げられる。一般に発生率が高いモータ91に関する異常要因の例として、ベアリングの劣化、絶縁の劣化、焼損、磁石の剥離、減磁などが挙げられる。
As yet another example, the
上述したように、正常/異常、製品寿命、または負荷の推定で用いられる閾値は、学習済みモデルの生成に基づいて設定されてもよい。この場合には、推定部15はその閾値を例えばリファレンス分布記憶部16から読み出して利用する。
As described above, the threshold value used for estimating normal / abnormal, product life, or load may be set based on the generation of the trained model. In this case, the
ステップS17では、推定部15が推定結果を出力する。例えば、推定部15は推定結果を、ストレージ163などの記録媒体に格納してもよい。あるいは、推定部15はテキスト、コンピュータグラフィック(CG)による動画または静止画などの形式で推定結果をモニタ120上に表示してもよい。
In step S17, the
ステップS18として示すように、電力変換システム1はステップS14以降の処理を繰り返し実行してもよい。例えば、電力変換システム1は機械9が動作し続けている間において所与の間隔でステップS14以降の処理を繰り返し実行してもよい。この繰り返し処理では、カレント分布生成部13はステップS14において新たな現在信号を取得し、ステップS15においてその現在信号に基づいて新たなカレント分布情報を生成する。推定部15はステップS16において、そのカレント分布情報とリファレンス分布情報とに基づいて機械9の現在状態を推定し、ステップS17においてその推定結果を出力する。
As shown in step S18, the
上述したように、リファレンス分布生成部21はステップS14~S17の一連の処理と並行してリファレンス分布情報を更新してもよい。例えば、リファレンス分布生成部21はステップS14で取得された現在信号を用いてリファレンス分布情報を更新し、必要であれば閾値も更新する。更新されたリファレンス分布情報(および、もしあれば、更新された閾値)は、その後の新たな現在信号に基づく推定において利用される。リファレンス分布生成部21は、ステップS14で取得された現在信号に基づく推定において機械9が正常であると判定された場合に限って、その現在信号を用いてリファレンス分布情報(および閾値)を更新してもよい。
As described above, the reference
[プログラム]
電力変換システム1の各機能モジュールは、プロセッサ161またはメモリ162の上に電力変換プログラムを読み込ませてプロセッサ161にそのプログラムを実行させることで実現される。電力変換プログラムは、電力変換システム1の各機能モジュールを実現するためのコードを含む。プロセッサ161は電力変換プログラムに従って入出力ポート164または通信ポート165を動作させ、メモリ162またはストレージ163におけるデータの読み出しおよび書き込みを実行する。このような処理により電力変換システム1の各機能モジュールが実現される。
[program]
Each functional module of the
電力変換プログラムは、CD-ROM、DVD-ROM、半導体メモリなどの非一時的な記録媒体に固定的に記録された上で提供されてもよい。あるいは、電力変換プログラムは、搬送波に重畳されたデータ信号として通信ネットワークを介して提供されてもよい。 The power conversion program may be provided after being fixedly recorded on a non-temporary recording medium such as a CD-ROM, a DVD-ROM, or a semiconductor memory. Alternatively, the power conversion program may be provided via a communication network as a data signal superimposed on a carrier wave.
[効果]
以上説明したように、本開示の一側面に係る電力変換システムは、機械のモータに電力を供給する電力変換装置を有する。電力変換システムは、機械の現在の動作を示す現在信号に基づいて、該現在信号の周波数成分の確率分布であるカレント分布に関するカレント分布情報を生成するカレント分布生成部と、機械の過去の動作を示す過去信号の周波数成分に基づく確率分布であるリファレンス分布に関するリファレンス分布情報とカレント分布情報との差異に基づいて、機械の現在状態を推定する推定部とを備える。
[effect]
As described above, the power conversion system according to one aspect of the present disclosure includes a power conversion device that supplies power to the motor of the machine. The power conversion system produces a current distribution generator that generates current distribution information regarding the current distribution, which is a probability distribution of the frequency components of the current signal, based on the current signal indicating the current operation of the machine, and a past operation of the machine. It is provided with an estimation unit that estimates the current state of the machine based on the difference between the reference distribution information and the current distribution information regarding the reference distribution, which is a probability distribution based on the frequency component of the past signal shown.
本開示の一側面に係る電力変換装置は、機械のモータに電力を供給する。電力変換装置は、機械の現在の動作を示す現在信号に基づいて、該現在信号の周波数成分の確率分布であるカレント分布に関するカレント分布情報を生成するカレント分布生成部と、機械の過去の動作を示す過去信号の周波数成分に基づく確率分布であるリファレンス分布に関するリファレンス分布情報とカレント分布情報との差異に基づいて、機械の現在状態を推定する推定部とを備える。 The power converter according to one aspect of the present disclosure supplies power to the motor of the machine. The power conversion device generates current distribution information regarding the current distribution, which is a probability distribution of the frequency components of the current signal, based on the current signal indicating the current operation of the machine, and a current distribution generator that generates the past operation of the machine. It is provided with an estimation unit that estimates the current state of the machine based on the difference between the reference distribution information and the current distribution information regarding the reference distribution, which is a probability distribution based on the frequency component of the past signal shown.
本開示の一側面に係る状態推定装置は、機械の現在の動作を示す現在信号に基づいて、該現在信号の周波数成分の確率分布であるカレント分布に関するカレント分布情報を生成するカレント分布生成部と、機械の過去の動作を示す過去信号の周波数成分に基づく確率分布であるリファレンス分布に関するリファレンス分布情報とカレント分布情報との差異に基づいて、機械の現在状態を推定する推定部とを備える。 The state estimation device according to one aspect of the present disclosure includes a current distribution generator that generates current distribution information regarding a current distribution, which is a probability distribution of frequency components of the current signal, based on a current signal indicating the current operation of the machine. It is provided with an estimation unit that estimates the current state of the machine based on the difference between the reference distribution information and the current distribution information regarding the reference distribution, which is a probability distribution based on the frequency component of the past signal indicating the past operation of the machine.
本開示の一側面に係る電力変換方法は、機械のモータに電力を供給する電力変換装置を有する電力変換システムにより実行される。電力変換方法は、機械の現在の動作を示す現在信号に基づいて、該現在信号の周波数成分の確率分布であるカレント分布に関するカレント分布情報を生成するステップと、機械の過去の動作を示す過去信号の周波数成分に基づく確率分布であるリファレンス分布に関するリファレンス分布情報とカレント分布情報との差異に基づいて、機械の現在状態を推定するステップとを含む。 The power conversion method according to one aspect of the present disclosure is executed by a power conversion system having a power conversion device that supplies power to the motor of the machine. The power conversion method includes a step of generating current distribution information regarding a current distribution, which is a probability distribution of frequency components of the current signal, based on a current signal indicating the current operation of the machine, and a past signal indicating the past operation of the machine. It includes a step of estimating the current state of the machine based on the difference between the reference distribution information and the current distribution information regarding the reference distribution, which is a probability distribution based on the frequency component of.
本開示の一側面に係る電力変換プログラムは、機械のモータに電力を供給する電力変換装置を有する電力変換システムとしてコンピュータシステムを機能させる。電力変換プログラムは、機械の現在の動作を示す現在信号に基づいて、該現在信号の周波数成分の確率分布であるカレント分布に関するカレント分布情報を生成するステップと、機械の過去の動作を示す過去信号の周波数成分に基づく確率分布であるリファレンス分布に関するリファレンス分布情報とカレント分布情報との差異に基づいて、機械の現在状態を推定するステップとをコンピュータシステムに実行させる。 The power conversion program according to one aspect of the present disclosure causes a computer system to function as a power conversion system having a power conversion device that supplies power to a machine motor. The power conversion program has a step of generating current distribution information regarding the current distribution, which is a probability distribution of the frequency component of the current signal, based on the current signal indicating the current operation of the machine, and a past signal indicating the past operation of the machine. The computer system is made to perform a step of estimating the current state of the machine based on the difference between the reference distribution information and the current distribution information regarding the reference distribution, which is a probability distribution based on the frequency component of.
このような側面においては、機械の現在の動作を示す確率分布と、機械の過去の動作に基づく確率分布との差異に基づいて機械の現在状態が推定される。確率分布を用いることで、機械の状態に関する推定の確からしさも含めて現在の状態と過去の状態とが比較されるので、機械の現在状態を適切に推定できる。例えば、確率分布を用いることで、個々の機械の特性に影響されることなく機械の現在状態を推定できる。この推定によって、機械の修理、機械の異常の原因究明などの作業の効率を上げることができる。 In such an aspect, the current state of the machine is estimated based on the difference between the probability distribution indicating the current operation of the machine and the probability distribution based on the past operation of the machine. By using the probability distribution, the current state and the past state are compared with each other, including the certainty of estimation regarding the state of the machine, so that the current state of the machine can be estimated appropriately. For example, by using a probability distribution, the current state of a machine can be estimated without being affected by the characteristics of each machine. This estimation can improve the efficiency of work such as repairing machines and investigating the causes of machine abnormalities.
他の側面に係る電力変換システムは、所定のパターンで電力変換装置を動作させる電力変換制御部をさらに備えてもよい。カレント分布生成部は、所定のパターンで電力変換装置を動作させた際の現在信号に基づいて、カレント分布情報を生成してもよく、推定部は、所定のパターンで電力変換装置を動作させた際のリファレンス分布情報とカレント分布情報との差異に基づいて、機械の現在状態を推定してもよい。同一のパターンに対応する二つの確率分布を比較することで、推定の精度を高めることができる。 The power conversion system according to the other aspect may further include a power conversion control unit that operates the power conversion device in a predetermined pattern. The current distribution generation unit may generate current distribution information based on the current signal when the power conversion device is operated in a predetermined pattern, and the estimation unit operates the power conversion device in a predetermined pattern. The current state of the machine may be estimated based on the difference between the reference distribution information and the current distribution information. By comparing two probability distributions corresponding to the same pattern, the accuracy of estimation can be improved.
他の側面に係る電力変換システムは、機械の複数の種類に対応する電力変換装置の複数の制御モードから、少なくとも一つの制御モードを設定する制御モード設定部と、少なくとも一つの制御モードに対応するリファレンス分布情報を選択するリファレンス分布選択部とをさらに備えてもよい。推定部は、選択されたリファレンス分布情報とカレント分布情報との差異に基づいて、機械の現在状態を推定してもよい。電力変換装置が有する複数の制御モードのそれぞれに対応するようにリファレンス分布が用意されるので、電力変換装置の実際の制御モードに応じて機械の現在状態を適切に推定できる。 The power conversion system according to the other aspect corresponds to a control mode setting unit that sets at least one control mode from a plurality of control modes of the power conversion device corresponding to a plurality of types of machines, and at least one control mode. A reference distribution selection unit for selecting reference distribution information may be further provided. The estimator may estimate the current state of the machine based on the difference between the selected reference distribution information and the current distribution information. Since the reference distribution is prepared so as to correspond to each of the plurality of control modes of the power converter, the current state of the machine can be appropriately estimated according to the actual control mode of the power converter.
他の側面に係る電力変換システムは、リファレンス分布情報を記憶する記憶部と、リファレンス分布情報を機械の情報に基づいて調整する調整部とをさらに備えてもよい。推定部は、調整されたリファレンス分布情報とカレント分布情報との差異に基づいて機械の現在状態を推定してもよい。 The power conversion system according to the other aspect may further include a storage unit that stores reference distribution information and an adjustment unit that adjusts reference distribution information based on machine information. The estimator may estimate the current state of the machine based on the difference between the adjusted reference distribution information and the current distribution information.
他の側面に係る電力変換装置は、リファレンス分布情報を記憶する記憶部と、リファレンス分布情報を機械の情報に基づいて調整する調整部とをさらに備えてもよい。推定部は、調整されたリファレンス分布情報とカレント分布情報との差異に基づいて機械の現在状態を推定してもよい。 The power conversion device according to another aspect may further include a storage unit that stores reference distribution information and an adjustment unit that adjusts reference distribution information based on machine information. The estimator may estimate the current state of the machine based on the difference between the adjusted reference distribution information and the current distribution information.
このような側面においては、機械の特性を考慮したリファレンス分布が用意されるので、推定の精度を高めることができる。 In this aspect, a reference distribution that takes into account the characteristics of the machine is prepared, so the accuracy of estimation can be improved.
他の側面に係る電力変換システムでは、電力変換装置はカレント分布生成部および推定部を備えてもよい。電力変換システムは、リファレンス分布情報を電力変換装置に送信するリファレンス装置をさらに備えてもよい。電力変換装置がカレント分布情報の生成と機械の現在状態の推定とを実行するので、その推定のために別個のハードウェアリソースを導入する必要がない。その分、電力変換システムを安価にかつ容易に構築できる。 In the power conversion system according to the other aspect, the power conversion device may include a current distribution generation unit and an estimation unit. The power conversion system may further include a reference device that transmits reference distribution information to the power conversion device. Since the power converter performs the generation of current distribution information and the estimation of the current state of the machine, there is no need to introduce separate hardware resources for that estimation. Therefore, the power conversion system can be constructed inexpensively and easily.
他の側面に係る電力変換システムは、過去信号および現在信号に基づいてリファレンス分布情報を生成するリファレンス分布生成部をさらに備えてもよい。この場合には、カレント分布と比較されるリファレンス分布が過去信号だけでなく現在信号も考慮して生成される。したがって、双方の確率分布の差異を適切に求めて、機械の現在状態を精度良く推定し続けることができる。 The power conversion system according to the other aspect may further include a reference distribution generation unit that generates reference distribution information based on past signals and current signals. In this case, the reference distribution to be compared with the current distribution is generated considering not only the past signal but also the current signal. Therefore, the difference between the two probability distributions can be appropriately obtained, and the current state of the machine can be continuously estimated with high accuracy.
他の側面に係る電力変換システムでは、リファレンス分布生成部は、過去信号に基づいて生成され、現在信号が入力されるとリファレンス分布情報を出力する学習済みモデルに基づいて、リファレンス分布情報を生成してもよい。学習済みモデルを用いることでリファレンス分布の精度が向上するので、機械の現在状態を精度良く推定することができる。 In the power conversion system according to the other aspect, the reference distribution generator generates the reference distribution information based on the trained model which is generated based on the past signal and outputs the reference distribution information when the current signal is input. You may. Since the accuracy of the reference distribution is improved by using the trained model, the current state of the machine can be estimated accurately.
他の側面に係る電力変換システムでは、リファレンス分布生成部は、過去信号の周波数成分に基づいて生成され、現在信号の周波数成分が入力されるとリファレンス分布情報を出力する学習済みモデルに基づいて、リファレンス分布情報を生成してもよい。現在信号の周波数成分を考慮することで、現在信号の変化の傾向を反映したリファレンス分布情報が生成される。このリファレンス分布情報を用いることで推定の精度を高めることができる。 In the power conversion system according to the other aspect, the reference distribution generator is generated based on the frequency component of the past signal, and is based on a trained model that outputs the reference distribution information when the frequency component of the current signal is input. Reference distribution information may be generated. By considering the frequency component of the current signal, reference distribution information that reflects the tendency of the change of the current signal is generated. The accuracy of estimation can be improved by using this reference distribution information.
他の側面に係る電力変換システムは、機械の複数の種類に対応する電力変換装置の複数の制御モードから、少なくとも一つの制御モードを設定する制御モード設定部と、少なくとも一つの制御モードに対応する学習済みモデルを選択するモデル選択部とをさらに備えてもよい。リファレンス分布生成部は、選択された学習済みモデルに基づいてリファレンス分布情報を生成してもよい。電力変換装置の制御モードに対応する学習済みモデルを用いてリファレンス分布情報が生成されるので、電力変換装置の実際の制御モードに応じて機械の現在状態を精度良く推定できる。 The power conversion system according to the other aspect corresponds to a control mode setting unit that sets at least one control mode from a plurality of control modes of the power conversion device corresponding to a plurality of types of machines, and at least one control mode. It may further include a model selection unit that selects a trained model. The reference distribution generator may generate reference distribution information based on the selected trained model. Since the reference distribution information is generated using the trained model corresponding to the control mode of the power converter, the current state of the machine can be estimated accurately according to the actual control mode of the power converter.
他の側面に係る電力変換システムでは、推定部は、差異と、学習済みモデルの生成に基づいて設定された閾値との比較に基づいて、機械が正常であるか異常であるかを判定し、該判定の結果を機械の現在状態として推定してもよい。学習済みモデルの生成に基づいて設定された閾値は、人の経験則に依ることなく客観的に設定された基準値であるといえる。この閾値を用いることで、機械が正常であるか否かを客観的に判定できる。 In the power conversion system according to the other aspect, the estimator determines whether the machine is normal or abnormal based on the comparison of the difference with the threshold set based on the generation of the trained model. The result of the determination may be estimated as the current state of the machine. It can be said that the threshold value set based on the generation of the trained model is a reference value set objectively without depending on the human empirical rule. By using this threshold value, it is possible to objectively determine whether or not the machine is normal.
他の側面に係る電力変換システムでは、推定部は、学習済みモデルの生成に基づいて設定された閾値からの差異の乖離度に基づいて、機械の製品寿命を判定し、該判定の結果を機械の現在状態として推定してもよい。学習済みモデルの生成に基づいて設定された閾値は、人の経験則に依ることなく客観的に設定された基準値であるといえる。この閾値を用いることで機械の製品寿命を客観的に判定できる。 In the power conversion system according to the other aspect, the estimation unit determines the product life of the machine based on the degree of deviation of the difference from the threshold value set based on the generation of the trained model, and the result of the determination is the machine. It may be estimated as the current state of. It can be said that the threshold value set based on the generation of the trained model is a reference value set objectively without depending on the human empirical rule. By using this threshold value, the product life of the machine can be objectively determined.
他の側面に係る電力変換システムでは、カレント分布生成部は、リファレンス分布生成部よりも計算コストが少ない計算方法によってカレント分布情報を生成してもよい。この構成によって、電力変換システムにおける計算量を削減しつつ推定の精度を高めることができる。 In the power conversion system related to the other aspect, the current distribution generation unit may generate the current distribution information by a calculation method having a lower calculation cost than the reference distribution generation unit. With this configuration, it is possible to improve the accuracy of estimation while reducing the amount of calculation in the power conversion system.
他の側面に係る電力変換システムでは、推定部は、差異と機械の異常要因との所与の関係に基づいて、差異に対応する異常要因を機械の現在状態として推定してもよい。この構成によって機械の異常要因を詳しく推定できる。 In the power conversion system according to the other aspect, the estimation unit may estimate the abnormal factor corresponding to the difference as the current state of the machine based on the given relationship between the difference and the abnormal factor of the machine. With this configuration, the cause of machine abnormality can be estimated in detail.
他の側面に係る電力変換システムでは、カレント分布生成部は、現在信号の周波数成分に基づくベイズ推定を実行して、カレント分布情報を生成してもよい。ベイズ推定を用いることで、サンプルデータが少ない場合でもカレント分布を精度良く求めることができる。また、限られたハードウェア資源上で確率分布を計算することができる。加えて、処理を繰り返すほど計算の精度を上げることが可能になる。 In the power conversion system according to the other aspect, the current distribution generator may execute Bayesian estimation based on the frequency component of the current signal to generate the current distribution information. By using Bayesian inference, the current distribution can be obtained accurately even when the sample data is small. In addition, the probability distribution can be calculated on limited hardware resources. In addition, the accuracy of the calculation can be improved as the processing is repeated.
[変形例]
以上、本開示での実施形態に基づいて詳細に説明した。しかし、本開示は上記実施形態に限定されるものではない。本開示は、その要旨を逸脱しない範囲で様々な変形が可能である。
[Modification example]
The above description has been made in detail based on the embodiments in the present disclosure. However, the present disclosure is not limited to the above embodiment. The present disclosure can be modified in various ways without departing from its gist.
本開示に係る状態推定装置は、電力変換装置とは異なる装置に適用されてもよい。例えば、その状態推定装置は、推定対象の状態が信号の周波数に現われるような構成に適用されてもよい。一方で、上記実施形態で述べた電力変換装置は、機械のモータに電力を供給するという観点から、機械の現在状態に直接的に関係する機器である。したがって、状態推定装置を電力変換装置に適用することで、電力変換システムにおけるハードウェアリソースを全体として節約しつつ、機械の現在状態を精度良く推定できる。 The state estimation device according to the present disclosure may be applied to a device different from the power conversion device. For example, the state estimation device may be applied to a configuration in which the state to be estimated appears at the frequency of the signal. On the other hand, the power conversion device described in the above embodiment is a device directly related to the current state of the machine from the viewpoint of supplying electric power to the motor of the machine. Therefore, by applying the state estimation device to the power conversion device, it is possible to accurately estimate the current state of the machine while saving the hardware resources in the power conversion system as a whole.
電力変換システムの構成は上記実施形態に限定されない。例えば、リファレンス装置は電力変換システムとは別のコンピュータシステムまたは制御システムに存在してもよい。この場合には、電力変換システムと該別システムとが通信ネットワークを介して接続されて、上記実施形態と同様の機能および処理が実行される。リファレンス装置の機能は電力変換装置または状態推定装置に組み込まれてもよい。上記実施形態では電力変換装置10が調整部18を備えるが、この調整部は省略されてもよい。電力変換装置の制御モードが一つである場合には、制御モード毎に処理を分ける必要はない。
The configuration of the power conversion system is not limited to the above embodiment. For example, the reference device may reside in a computer system or control system separate from the power conversion system. In this case, the power conversion system and the other system are connected via a communication network, and the same functions and processes as those in the above embodiment are executed. The function of the reference device may be incorporated into the power conversion device or the state estimation device. In the above embodiment, the
システムのハードウェア構成は、プログラムの実行により各機能モジュールを実現する態様に限定されない。例えば、上記実施形態における機能モジュールの少なくとも一部が、その機能に特化した論理回路により構成されていてもよいし、該論理回路を集積したASIC(Application Specific Integrated Circuit)により構成されてもよい。 The hardware configuration of the system is not limited to the mode in which each functional module is realized by executing the program. For example, at least a part of the functional module in the above embodiment may be configured by a logic circuit specialized for the function, or may be configured by an ASIC (Application Specific Integrated Circuit) in which the logic circuit is integrated. ..
少なくとも一つのプロセッサにより実行される方法の処理手順は上記実施形態での例に限定されない。例えば、上述したステップ(処理)の一部が省略されてもよいし、別の順序で各ステップが実行されてもよい。また、上述したステップのうちの任意の2以上のステップが組み合わされてもよいし、ステップの一部が修正または削除されてもよい。あるいは、上記の各ステップに加えて他のステップが実行されてもよい。 The processing procedure of the method executed by at least one processor is not limited to the example in the above embodiment. For example, some of the steps (processes) described above may be omitted, or each step may be executed in a different order. In addition, any two or more steps of the above-mentioned steps may be combined, or a part of the steps may be modified or deleted. Alternatively, other steps may be performed in addition to each of the above steps.
コンピュータシステムまたはコンピュータ内で二つの数値の大小関係を比較する際には、「以上」および「よりも大きい」という二つの基準のどちらを用いてもよく、「以下」および「未満」という二つの基準のうちのどちらを用いてもよい。 When comparing the magnitude relations of two numbers in a computer system or computer, either of the two criteria "greater than or equal to" and "greater than" may be used, and the two criteria "less than or equal to" and "less than" Either of the criteria may be used.
1…電力変換システム、10…電力変換装置、20…リファレンス装置、11…制御モード設定部、12…電力変換制御部、13…カレント分布生成部、14…リファレンス分布設定部、15…推定部、16…リファレンス分布記憶部、17…リファレンス分布選択部、18…調整部、21…リファレンス分布生成部、22…モデルデータベース、23…モデル選択部、9…機械、91…モータ、92…駆動対象、93…センサ、100…コンピュータ、110…本体、120…モニタ、130…入力デバイス。 1 ... power conversion system, 10 ... power conversion device, 20 ... reference device, 11 ... control mode setting unit, 12 ... power conversion control unit, 13 ... current distribution generation unit, 14 ... reference distribution setting unit, 15 ... estimation unit, 16 ... Reference distribution storage unit, 17 ... Reference distribution selection unit, 18 ... Adjustment unit, 21 ... Reference distribution generation unit, 22 ... Model database, 23 ... Model selection unit, 9 ... Machine, 91 ... Motor, 92 ... Drive target, 93 ... sensor, 100 ... computer, 110 ... main unit, 120 ... monitor, 130 ... input device.
Claims (19)
前記機械の現在の動作を示す現在信号に基づいて、該現在信号の周波数成分の確率分布であるカレント分布に関するカレント分布情報を生成するカレント分布生成部と、
前記機械の過去の動作を示す過去信号の周波数成分に基づく確率分布であるリファレンス分布に関するリファレンス分布情報と前記カレント分布情報との差異に基づいて、前記機械の現在状態を推定する推定部と、
を備える電力変換システム。 A power conversion system that has a power conversion device that supplies power to the motor of a machine.
A current distribution generator that generates current distribution information regarding the current distribution, which is a probability distribution of the frequency components of the current signal, based on the current signal indicating the current operation of the machine.
An estimation unit that estimates the current state of the machine based on the difference between the reference distribution information regarding the reference distribution, which is a probability distribution based on the frequency component of the past signal indicating the past operation of the machine, and the current distribution information.
Power conversion system with.
前記カレント分布生成部は、前記所定のパターンで前記電力変換装置を動作させた際の前記現在信号に基づいて、前記カレント分布情報を生成し、
前記推定部は、前記所定のパターンで前記電力変換装置を動作させた際の前記リファレンス分布情報と前記カレント分布情報との差異に基づいて、前記機械の現在状態を推定する、
請求項1に記載の電力変換システム。 A power conversion control unit that operates the power conversion device in a predetermined pattern is further provided.
The current distribution generation unit generates the current distribution information based on the current signal when the power conversion device is operated in the predetermined pattern.
The estimation unit estimates the current state of the machine based on the difference between the reference distribution information and the current distribution information when the power conversion device is operated in the predetermined pattern.
The power conversion system according to claim 1.
前記少なくとも一つの制御モードに対応する前記リファレンス分布情報を選択するリファレンス分布選択部と、
をさらに備え、
前記推定部は、前記選択されたリファレンス分布情報と前記カレント分布情報との差異に基づいて、前記機械の現在状態を推定する、
請求項1または2に記載の電力変換システム。 A control mode setting unit that sets at least one control mode from a plurality of control modes of the power conversion device corresponding to a plurality of types of the machine.
A reference distribution selection unit that selects the reference distribution information corresponding to at least one control mode, and a reference distribution selection unit.
With more
The estimation unit estimates the current state of the machine based on the difference between the selected reference distribution information and the current distribution information.
The power conversion system according to claim 1 or 2.
前記リファレンス分布情報を前記機械の情報に基づいて調整する調整部と、
をさらに備え、
前記推定部は、前記調整されたリファレンス分布情報と前記カレント分布情報との差異に基づいて前記機械の現在状態を推定する、
請求項1~3のいずれか一項に記載の電力変換システム。 A storage unit that stores the reference distribution information and
An adjustment unit that adjusts the reference distribution information based on the information of the machine, and
With more
The estimation unit estimates the current state of the machine based on the difference between the adjusted reference distribution information and the current distribution information.
The power conversion system according to any one of claims 1 to 3.
前記電力変換システムは、前記リファレンス分布情報を前記電力変換装置に送信するリファレンス装置をさらに備える、
請求項1~4のいずれか一項に記載の電力変換システム。 The power conversion device includes the current distribution generation unit and the estimation unit.
The power conversion system further includes a reference device that transmits the reference distribution information to the power conversion device.
The power conversion system according to any one of claims 1 to 4.
請求項6に記載の電力変換システム。 The reference distribution generation unit generates the reference distribution information based on a learned model that is generated based on the past signal and outputs the reference distribution information when the current signal is input.
The power conversion system according to claim 6.
請求項7に記載の電力変換システム。 The reference distribution generation unit generates the reference distribution information based on the trained model that is generated based on the frequency component of the past signal and outputs the reference distribution information when the frequency component of the current signal is input. Generate,
The power conversion system according to claim 7.
前記少なくとも一つの制御モードに対応する前記学習済みモデルを選択するモデル選択部と、
をさらに備え、
前記リファレンス分布生成部は、前記選択された学習済みモデルに基づいて前記リファレンス分布情報を生成する、
請求項7または8に記載の電力変換システム。 A control mode setting unit that sets at least one control mode from a plurality of control modes of the power conversion device corresponding to a plurality of types of the machine.
A model selection unit that selects the trained model corresponding to at least one control mode, and
With more
The reference distribution generation unit generates the reference distribution information based on the selected trained model.
The power conversion system according to claim 7 or 8.
請求項7~9のいずれか一項に記載の電力変換システム。 The estimation unit determines whether the machine is normal or abnormal based on the comparison between the difference and the threshold value set based on the generation of the trained model, and determines whether the machine is normal or abnormal, and determines the result of the determination. Estimate as the current state of the machine,
The power conversion system according to any one of claims 7 to 9.
請求項7~10のいずれか一項に記載の電力変換システム。 The estimation unit determines the product life of the machine based on the degree of deviation of the difference from the threshold value set based on the generation of the trained model, and estimates the result of the determination as the current state of the machine. do,
The power conversion system according to any one of claims 7 to 10.
請求項6~11のいずれか一項に記載の電力変換システム。 The current distribution generation unit generates the current distribution information by a calculation method having a lower calculation cost than the reference distribution generation unit.
The power conversion system according to any one of claims 6 to 11.
請求項1~12のいずれか一項に記載の電力変換システム。 The estimation unit estimates the abnormal factor corresponding to the difference as the current state of the machine based on a given relationship between the difference and the abnormal factor of the machine.
The power conversion system according to any one of claims 1 to 12.
請求項1~13のいずれか一項に記載の電力変換システム。 The current distribution generator executes Bayesian estimation based on the frequency component of the current signal to generate the current distribution information.
The power conversion system according to any one of claims 1 to 13.
前記機械の現在の動作を示す現在信号に基づいて、該現在信号の周波数成分の確率分布であるカレント分布に関するカレント分布情報を生成するカレント分布生成部と、
前記機械の過去の動作を示す過去信号の周波数成分に基づく確率分布であるリファレンス分布に関するリファレンス分布情報と前記カレント分布情報との差異に基づいて、前記機械の現在状態を推定する推定部と、
を備える電力変換装置。 A power converter that supplies power to the motor of a machine.
A current distribution generator that generates current distribution information regarding the current distribution, which is a probability distribution of the frequency components of the current signal, based on the current signal indicating the current operation of the machine.
An estimation unit that estimates the current state of the machine based on the difference between the reference distribution information regarding the reference distribution, which is a probability distribution based on the frequency component of the past signal indicating the past operation of the machine, and the current distribution information.
A power converter equipped with.
前記リファレンス分布情報を前記機械の情報に基づいて調整する調整部と、
をさらに備え、
前記推定部は、前記調整されたリファレンス分布情報と前記カレント分布情報との差異に基づいて前記機械の現在状態を推定する、
請求項15に記載の電力変換装置。 A storage unit that stores the reference distribution information and
An adjustment unit that adjusts the reference distribution information based on the information of the machine, and
With more
The estimation unit estimates the current state of the machine based on the difference between the adjusted reference distribution information and the current distribution information.
The power conversion device according to claim 15.
前記機械の過去の動作を示す過去信号の周波数成分に基づく確率分布であるリファレンス分布に関するリファレンス分布情報と前記カレント分布情報との差異に基づいて、前記機械の現在状態を推定する推定部と、
を備える状態推定装置。 A current distribution generator that generates current distribution information regarding the current distribution, which is a probability distribution of the frequency components of the current signal, based on the current signal indicating the current operation of the machine.
An estimation unit that estimates the current state of the machine based on the difference between the reference distribution information regarding the reference distribution, which is a probability distribution based on the frequency component of the past signal indicating the past operation of the machine, and the current distribution information.
A state estimator comprising.
前記機械の現在の動作を示す現在信号に基づいて、該現在信号の周波数成分の確率分布であるカレント分布に関するカレント分布情報を生成するステップと、
前記機械の過去の動作を示す過去信号の周波数成分に基づく確率分布であるリファレンス分布に関するリファレンス分布情報と前記カレント分布情報との差異に基づいて、前記機械の現在状態を推定するステップと、
を含む電力変換方法。 A power conversion method performed by a power conversion system having a power conversion device that supplies power to the motor of a machine.
A step of generating current distribution information regarding a current distribution, which is a probability distribution of frequency components of the current signal, based on a current signal indicating the current operation of the machine.
A step of estimating the current state of the machine based on the difference between the reference distribution information regarding the reference distribution, which is a probability distribution based on the frequency component of the past signal indicating the past operation of the machine, and the current distribution information.
Power conversion method including.
前記機械の現在の動作を示す現在信号に基づいて、該現在信号の周波数成分の確率分布であるカレント分布に関するカレント分布情報を生成するステップと、
前記機械の過去の動作を示す過去信号の周波数成分に基づく確率分布であるリファレンス分布に関するリファレンス分布情報と前記カレント分布情報との差異に基づいて、前記機械の現在状態を推定するステップと、
を前記コンピュータシステムに実行させる電力変換プログラム。 A power conversion program that causes a computer system to function as a power conversion system that has a power conversion device that supplies power to the motors of a machine.
A step of generating current distribution information regarding a current distribution, which is a probability distribution of frequency components of the current signal, based on a current signal indicating the current operation of the machine.
A step of estimating the current state of the machine based on the difference between the reference distribution information regarding the reference distribution, which is a probability distribution based on the frequency component of the past signal indicating the past operation of the machine, and the current distribution information.
A power conversion program that causes the computer system to execute.
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| JP2019028765A (en) * | 2017-07-31 | 2019-02-21 | 株式会社安川電機 | Power conversion device, server, and data generation method |
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| WO2015079554A1 (en) * | 2013-11-29 | 2015-06-04 | 株式会社日立製作所 | Device for estimating state of power grid, state estimation method thereof, and power grid control system |
| JP2019028765A (en) * | 2017-07-31 | 2019-02-21 | 株式会社安川電機 | Power conversion device, server, and data generation method |
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