CN119958762A

CN119958762A - Computer-aided pressure transmitter fault diagnosis method and system

Info

Publication number: CN119958762A
Application number: CN202510437497.1A
Authority: CN
Inventors: 曲桂双; 刘灿; 杨宏; 梁兵
Original assignee: Shenzhen Te'an Industrial Technology Co ltd
Current assignee: Shenzhen Te'an Industrial Technology Co ltd
Priority date: 2025-04-09
Filing date: 2025-04-09
Publication date: 2025-05-09
Anticipated expiration: 2045-04-09
Also published as: CN119958762B

Abstract

The present invention relates to the field of equipment maintenance, and discloses a computer-aided pressure transmitter fault diagnosis method and system, including: first obtaining real-time sensor data of the pressure transmitter, analyzing its dynamic parameter characteristics, constructing a multi-dimensional parameter matrix and extracting trend characteristics, combining historical records to perform initial fault location, identifying core fault types and calculating fault intensity indexes, and then delineating high-risk fault areas based on this, calibrating and testing output signals, determining key maintenance areas, and then querying component aging data in the area, analyzing key failure modes, extracting maintenance monitoring points to calculate health status indexes, and then generating an evaluation index set, identifying multi-factor coupling weights, and finally generating a full life cycle fault monitoring report. The present invention can improve the accuracy of pressure transmitter fault diagnosis.

Description

Computer-aided pressure transmitter fault diagnosis method and system

Technical Field

The invention relates to a fault diagnosis method and system for a computer-aided pressure transmitter, and belongs to the field of equipment maintenance.

Background

In a modern industrial production system, the pressure transmitter is used as key sensing equipment, is widely applied to the fields of petrochemical industry, electric power energy, metallurgical manufacturing and the like, bears the heavy duty of accurately measuring and transmitting pressure signals, and is one of the core links for guaranteeing the stable operation of industrial processes and ensuring the quality and production safety of products.

However, current conventional pressure transmitter fault diagnosis approaches have significant limitations. On one hand, manual inspection depends on experience and skill level of operation and maintenance personnel, so that the efficiency is low, the subjectivity is high, early potential faults are difficult to comprehensively and accurately find, on the other hand, a conventional automatic diagnosis method based on simple threshold judgment cannot adapt to complex and changeable industrial production environments, the recognition accuracy of the fault type and the fault degree of the pressure transmitter is limited, when complex conditions such as sensor aging, circuit parameter drift and complex working condition interference are met, the conventional diagnosis method is difficult to accurately judge faults in time, so that the fault detection and repair time is prolonged, and therefore, a computer-assisted pressure transmitter fault diagnosis method is needed, and the accuracy of pressure transmitter fault diagnosis is improved.

Disclosure of Invention

The invention provides a fault diagnosis method and a fault diagnosis system for a computer-aided pressure transmitter, and mainly aims to improve the accuracy of fault diagnosis of the pressure transmitter.

In order to achieve the above object, the present invention provides a computer-aided pressure transmitter fault diagnosis method, comprising:

Acquiring real-time sensing data of a pressure transmitter during operation, analyzing dynamic parameter characteristics corresponding to the real-time sensing data, constructing a multi-dimensional parameter matrix of the pressure transmitter in an operation state based on the dynamic parameter characteristics, and extracting trend related characteristics in the multi-dimensional parameter matrix;

Based on the trend-related characteristics and the history record data corresponding to the pressure transmitter, performing initial fault positioning on the pressure transmitter to obtain a fault positioning source point, identifying a core fault type corresponding to the fault positioning source point, and based on the core fault type, calculating a fault intensity index corresponding to the fault positioning source point;

based on the fault intensity index, defining a fault high-risk area corresponding to an internal circuit and a sensing unit of the pressure transmitter, performing signal zero calibration on output signals in the high-risk area to obtain calibration output signals, performing real-time performance detection on the calibration output signals to obtain a response performance curve, and determining a key maintenance area corresponding to the pressure transmitter based on the response performance curve;

Inquiring part aging data in the key maintenance area, analyzing a key failure mode corresponding to the key maintenance area according to the part aging data, extracting maintenance monitoring points in the key failure mode, and calculating a health state index corresponding to the key maintenance area based on the maintenance monitoring points;

Based on the health state index, generating an evaluation index set corresponding to the pressure transmitter, inquiring an index degradation trend corresponding to the evaluation index set, identifying a multi-factor coupling weight corresponding to the index degradation trend, and generating a fault monitoring report corresponding to the full life cycle of the pressure transmitter based on the multi-factor coupling weight.

Optionally, the constructing a multidimensional parameter matrix of the pressure transmitter in an operation state based on the dynamic parameter feature includes:

extracting a core variable corresponding to the dynamic parameter characteristic;

Generating a working condition time sequence corresponding to the pressure transmitter based on the core variable;

Carrying out sliding window segmentation on the working condition time sequence to obtain window data blocks;

performing cross-domain fusion on the data in the window data block to obtain a fusion data block;

identifying a corresponding multi-dimensional attribute of the fused data block;

And constructing a multi-dimensional parameter matrix of the pressure transmitter in an operation state based on the multi-dimensional attribute.

Optionally, the performing fault initial positioning on the pressure transmitter based on the trend-related features and combining the history record data corresponding to the pressure transmitter to obtain a fault positioning source point includes:

Determining a fault type mode corresponding to the pressure transmitter based on the trend-related characteristics and the history record data corresponding to the pressure transmitter;

extracting fault mode matching points in the fault type mode;

Inquiring a history high-emission component corresponding to the pressure transmitter based on the fault mode matching point;

performing association analysis on the historical high-incidence component to obtain a high-incidence association component;

and performing initial fault positioning on the high-incidence association component to obtain a fault positioning source point.

Optionally, the calculating, based on the core fault type, a fault strength index corresponding to the fault location source point includes:

Calculating a fault intensity index corresponding to the fault location source point by using the following formula:

;

wherein, Representing the fault intensity index corresponding to the fault location source point,Representing the number of fault factors associated with the core fault type,Indicating the number index corresponding to the fault factor,Represent the firstThe factor weights corresponding to the individual fault factors,Representing the actual measurement value corresponding to the ith fault factor,Represent the firstThe normal reference value corresponding to the individual fault factor,Represent the firstMaximum allowable fluctuation value corresponding to each fault factor,Indicating the period of time for which the monitoring is to be performed,Represent the firstThe individual fault factors are at the momentIs a fault affecting function of (1).

Optionally, the defining the fault high risk area of the internal circuit of the pressure transmitter corresponding to the sensing unit based on the fault intensity index includes:

analyzing the index composition weight corresponding to the fault intensity index;

Calculating a contribution intensity value corresponding to the sensing unit by an internal circuit of the pressure transmitter based on the index composition weight;

based on the contribution intensity value, sequencing the internal circuit and the sensing unit to obtain a sequencing result;

Marking a component exceeding a preset threshold in the sequencing result as a high-risk candidate object;

And based on the high-risk candidate object, defining a fault high-risk area corresponding to the pressure transmitter.

Optionally, the determining, based on the response performance curve, an important maintenance area corresponding to the pressure transmitter includes:

identifying an abnormal fluctuation segment in the response performance curve;

Marking a key time stamp corresponding to the abnormal fluctuation segment;

backtracking an operation log corresponding to the pressure transmitter based on the key time stamp;

inquiring an abnormal event record in the operation log;

positioning a fault triggering module corresponding to the pressure transmitter based on the abnormal event record;

based on the fault triggering module, determining an important maintenance area corresponding to the pressure transmitter

Optionally, the querying the component aging data in the key maintenance area includes:

Identifying a unique identification code corresponding to the part in the key maintenance area;

Based on the unique identification code, calling a basic information file corresponding to the part in the key maintenance area;

Extracting past maintenance records in the basic information file;

and inquiring the aging data of the components in the key maintenance area based on the past maintenance record.

Optionally, the calculating, based on the maintenance monitoring point, a health state index corresponding to the key maintenance area includes:

calculating the health state index corresponding to the key maintenance area by using the following formula:

;

wherein, Representing the health state index corresponding to the key maintenance area,Indicating the corresponding number of maintenance monitoring points,A number index corresponding to the maintenance monitoring point,Represent the firstThe state coefficients corresponding to the individual maintenance monitoring points,Represent the firstThe maintenance weights corresponding to the maintenance monitoring points,Indicating the number of critical components within the critical maintenance area,Indicating the corresponding number index of key components,Represent the firstPerformance degradation indicators corresponding to the individual critical components,Representing the number of external environmental factors in the critical maintenance area,A quantity index representing the external environmental factors,Represent the firstThe corresponding influence coefficients of the individual external environmental factors,Indicating the total length of time for maintenance,Representing the state impact function of time-varying temperature on the critical maintenance area.

Optionally, generating the evaluation index set corresponding to the pressure transmitter based on the health state index includes:

Dividing a state operation interval corresponding to the health state index;

extracting historical fault characteristics in the state operation interval;

constructing a state mapping table corresponding to the historical fault characteristics;

Performing hierarchical distribution on the state mapping table to obtain a state hierarchical index;

And generating an evaluation index set corresponding to the pressure transmitter based on the state level index.

In order to solve the above problems, the present invention also provides a computer-aided pressure transmitter fault diagnosis system, the system comprising:

The characteristic extraction module is used for acquiring real-time sensing data of the pressure transmitter in operation, analyzing dynamic parameter characteristics corresponding to the real-time sensing data, constructing a multi-dimensional parameter matrix of the pressure transmitter in an operation state based on the dynamic parameter characteristics, and extracting trend related characteristics in the multi-dimensional parameter matrix;

The index calculation module is used for initially positioning the fault of the pressure transmitter based on the trend-related characteristics and the history record data corresponding to the pressure transmitter to obtain a fault positioning source point, identifying a core fault type corresponding to the fault positioning source point, and calculating a fault intensity index corresponding to the fault positioning source point based on the core fault type;

The area determining module is used for defining a fault high-risk area corresponding to the internal circuit and the sensing unit of the pressure transmitter based on the fault intensity index, carrying out signal zero calibration on output signals in the high-risk area to obtain calibrated output signals, carrying out performance real-time detection on the calibrated output signals to obtain a response performance curve, and determining a key maintenance area corresponding to the pressure transmitter based on the response performance curve;

The state index module is used for inquiring the part aging data in the key maintenance area, analyzing a key failure mode corresponding to the key maintenance area according to the part aging data, extracting maintenance monitoring points in the key failure mode, and calculating a health state index corresponding to the key maintenance area based on the maintenance monitoring points;

The report generation module is used for generating an evaluation index set corresponding to the pressure transmitter based on the health state index, inquiring an index degradation trend corresponding to the evaluation index set, identifying multi-factor coupling weights corresponding to the index degradation trend, and generating a fault monitoring report corresponding to the full life cycle of the pressure transmitter based on the multi-factor coupling weights.

Compared with the prior art, the invention can timely detect the tiny change of the running state of the equipment by acquiring the real-time sensing data of the pressure transmitter during running and analyzing the dynamic parameter characteristics corresponding to the real-time sensing data, provides key basis for early warning of faults, is beneficial to deep understanding of the working characteristics of the equipment and further optimizes the running parameters, performs initial fault positioning on the pressure transmitter based on the trend related characteristics and the historical record data corresponding to the pressure transmitter to obtain fault positioning source points, can integrate the running information of the current and the past equipment and accurately lock the easily-appearing sources of the faults, thereby improving the fault checking efficiency, and is further based on the fault intensity index, the invention can accurately locate the problem area inside the pressure transmitter by defining the high risk area of faults corresponding to the internal circuit and the sensing unit of the pressure transmitter, is favorable for rapid focusing inspection key, improves the maintenance efficiency, avoids blindness of comprehensive inspection, can simultaneously carry out preventive maintenance on the high risk area in advance, reduces the probability of sudden faults and ensures the stable and reliable operation of the pressure transmitter, further, the invention can assist in judging the residual service life of the components by inquiring the aging data of the components in the key maintenance area, plan and replace in advance, prevent faults caused by sudden aging damage of the components, simultaneously can analyze the aging rule of the components according to the aging data, provides powerful support for optimizing the maintenance strategy of the equipment and improving the reliability of the whole operation, and finally, generates an evaluation index set corresponding to the pressure transmitter based on the health state index, can comprehensively, the operation condition of the pressure transmitter is quantitatively evaluated, potential problems can be rapidly positioned, scientific basis is provided for maintenance decision, maintenance resources are reasonably distributed, maintenance efficiency is improved, fault risk is reduced, and stable and reliable operation of the pressure transmitter is ensured. Therefore, the computer-aided pressure transmitter fault diagnosis method and system provided by the embodiment of the invention can improve the accuracy of pressure transmitter fault diagnosis.

Drawings

FIG. 1 is a flow chart of a method for fault diagnosis of a computer-aided pressure transmitter according to an embodiment of the present invention;

FIG. 2 is a block diagram of a system for implementing the computer-aided pressure transmitter fault diagnosis according to an embodiment of the present invention.

The achievement of the objects, functional features and advantages of the present invention will be further described with reference to the accompanying drawings, in conjunction with the embodiments.

Detailed Description

It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.

The embodiment of the application provides a fault diagnosis method for a computer-aided pressure transmitter. The main body of execution of the computer-aided pressure transmitter fault diagnosis method comprises, but is not limited to, at least one of a server, a terminal and the like which can be configured to execute the method provided by the embodiment of the application. In other words, the computer-aided pressure transmitter fault diagnosis method may be performed by software or hardware installed at a terminal device or a server device. The server side comprises, but is not limited to, a single server, a server cluster, a cloud server or a cloud server cluster and the like.

Example 1:

Referring to fig. 1, a flow chart of a fault diagnosis method for a computer-aided pressure transmitter according to an embodiment of the present invention is shown. In this embodiment, the computer-aided pressure transmitter fault diagnosis method includes:

S1, acquiring real-time sensing data of the pressure transmitter in operation, analyzing dynamic parameter characteristics corresponding to the real-time sensing data, constructing a multi-dimensional parameter matrix of the pressure transmitter in an operation state based on the dynamic parameter characteristics, and extracting trend related characteristics in the multi-dimensional parameter matrix.

According to the invention, by acquiring the real-time sensing data of the pressure transmitter during operation and analyzing the dynamic parameter characteristics corresponding to the real-time sensing data, the fine change of the operation state of the equipment can be timely perceived, a key basis is provided for early warning of faults, and secondly, accurate analysis of the dynamic parameter characteristics is beneficial to further understanding of the operation characteristics of the equipment, so that the operation parameters are optimized.

The pressure transmitter is widely applied in industrial production, for example, in petrochemical pipelines, can convert fluid pressure in the pipelines into standard electrical signals and provide key data for production regulation, the real-time sensing data is widely applied in industrial production, for example, in petrochemical pipelines, can convert fluid pressure in the pipelines into standard electrical signals and provide key data for production regulation, the dynamic parameter characteristic can refer to the change rate of a pressure value in a period of time, such as the pressure rise of 0.1MPa per minute or the frequency of pressure fluctuation, such as the fluctuation of 10 times per hour, and the like, the dynamic change condition of the running state of the equipment can be displayed, optionally, the acquisition of the real-time sensing data when the pressure transmitter is running can be realized through an adaptive sampling algorithm, such as dynamic adjustment of sampling intervals according to the change frequency of output signals of the pressure transmitter, shortening of the sampling intervals to acquire more accurate data when the signal changes severely, and increasing the sampling intervals and reducing the data transmission and storage pressure when the signal changes relatively stably, so that the real-time sensing data is acquired efficiently, and the analysis of the real-time sensing data can be realized through the dynamic parameter characteristic corresponding to the real-time sensing data, such as the dynamic parameter characteristic of the pressure sensor can be realized through a tool MATLAB, python.

Furthermore, the multi-dimensional parameter matrix of the pressure transmitter in the running state is constructed based on the dynamic parameter characteristics, complex and scattered equipment running information can be integrated to form comprehensive and structured data expression, a more efficient data processing basis is provided for subsequent fault diagnosis and analysis, and the accuracy and the efficiency of fault positioning and judging are greatly improved.

The multi-dimensional parameter matrix is a matrix constructed based on multi-dimensional attributes of the fusion data blocks, each row of the matrix represents one fusion data block, and each column corresponds to one multi-dimensional attribute of the fusion data block.

The method comprises the steps of extracting a core variable corresponding to the dynamic parameter characteristic, generating a working condition time sequence corresponding to the pressure transmitter based on the core variable, carrying out sliding window segmentation on the working condition time sequence to obtain window data blocks, carrying out cross-domain fusion on data in the window data blocks to obtain fusion data blocks, identifying corresponding multi-dimensional attributes of the fusion data blocks, and constructing the multi-dimensional parameter matrix of the pressure transmitter in the running state based on the multi-dimensional attributes.

The method comprises the steps of obtaining a working condition time sequence, wherein the working condition time sequence comprises a plurality of working condition time sequence data blocks, a window data block and a fusion data block, wherein the working condition time sequence data blocks are sequentially sliding on the working condition time sequence, the working condition time sequence data blocks are generated on the basis of the core variable, a series of data point sets are arranged according to time sequence and reflect the working condition of the pressure transmitter at different moments, each data point corresponds to the value of the core variable at a specific moment, the continuous change condition of the working condition of the pressure transmitter along with time can be clearly observed, the window data blocks are obtained by dividing a sliding window of the working condition time sequence, the sliding window is a time window with fixed size, data in each intercepting window serves as a window data block, each window data block comprises relevant data of the working of the pressure transmitter in a specific time period, and the fusion data blocks are data sets obtained after the cross-domain fusion of the data in the window data blocks. The cross-domain fusion refers to organically integrating data from different fields (such as a pressure measurement field, a temperature influence field and the like) in a window data block, comprehensively considering the influence of a plurality of factors on the operation state of the pressure transmitter, and the multi-dimensional attribute refers to characteristic attributes of a plurality of different aspects of the fusion data block, wherein the characteristics of the fusion data block are described from a plurality of angles, including but not limited to statistical attributes (such as mean value, variance, kurtosis and the like) of the data, frequency attributes (frequency components and distribution of signals), correlation attributes (correlation degree among different variables) and the like.

Further, the extraction of the core variable corresponding to the dynamic parameter characteristic can be achieved through a principal component analysis method, for example, the high-dimensional dynamic parameter characteristic is projected to a low-dimensional space, an original variable corresponding to the principal component with high contribution rate is selected as the core variable, the generation of the working condition time sequence corresponding to the pressure transmitter can be achieved through an interpolation algorithm, for example, linear interpolation or spline interpolation algorithm is adopted for supplementing missing data points which can exist in the time sequence, so as to obtain the working condition time sequence, sliding window segmentation of the working condition time sequence can be achieved through fixed window sliding, for example, a time window with a fixed size is set, point-by-point sliding is performed on the working condition time sequence, data in the window is intercepted each time, so as to obtain a window data block, cross-domain fusion of the data in the window data block can be achieved through a weighted fusion algorithm, for example, according to the influence degree of the data in different fields on the running state of the pressure transmitter, different weights are distributed for the data in each field, then weighted summation fusion is carried out, the corresponding multi-dimensional Fourier transform of the fusion data block can be achieved through the frequency-domain conversion block, for example, the multi-dimensional conversion block can be achieved through the frequency-domain conversion block and the frequency-domain conversion block can be achieved in the same as the matrix, the multi-dimensional conversion data represents the different-dimensional attribute is represented by the method, the performance of the performance matrix is obtained by the method, resulting in a multi-dimensional parameter matrix).

According to the invention, through extracting the trend related characteristics in the multidimensional parameter matrix, the long-term increasing and decreasing trend and periodic fluctuation of key indexes such as pressure, signals and the like can be easily captured, so that potential fault risks are predicted in advance, key clues are provided for preventive maintenance, and the power-assisted industrial production is more stable and efficient to operate.

The trend-related features are key information sets which are extracted from a multidimensional parameter matrix and can reflect the trend of the running state of the pressure transmitter along with the time. It covers monotonic features of the parameters, i.e. whether the parameters are continuously rising, falling or remain stationary, whereby the development of the performance of the device can be determined, and periodic features, e.g. whether there is regular periodic fluctuation of the pressure signal, which helps to find potential problems due to the operating period of the device, optionally the extracting trend-related features in the multi-dimensional parameter matrix can be done by moving average methods, e.g. smoothing the data by calculating moving averages of the data, eliminating short term fluctuations, highlighting long term trends, thus obtaining trend-related features.

S2, based on the trend-related features and the history record data corresponding to the pressure transmitter, performing initial fault positioning on the pressure transmitter to obtain a fault positioning source point, identifying a core fault type corresponding to the fault positioning source point, and based on the core fault type, calculating a fault intensity index corresponding to the fault positioning source point.

According to the invention, based on the trend-related characteristics and the history record data corresponding to the pressure transmitter, the pressure transmitter is initially positioned for faults to obtain the fault positioning source point, and the current and past equipment operation information can be synthesized, so that the source of faults easy to occur can be precisely locked, and the fault checking efficiency is improved.

The historical record data refer to various data sets accumulated in the past operation process of the pressure transmitter, and comprise operation parameters of equipment at different time points, such as pressure measurement values, temperatures, output signal intensity and the like, equipment maintenance records, such as maintenance time, maintenance content, replacement part information and the like, and fault records which occur once, such as fault occurrence time, fault phenomenon description, fault type and final solution, wherein the fault location source point refers to a starting position or a part of the occurrence of a fault in the pressure transmitter, which is finally determined through initial fault location of a high-altitude association component, is a key result of fault diagnosis, the root of the fault is defined, and once the fault location source point is determined, the part or the position can be specifically detected, maintained or replaced, so that the fault problem of the pressure transmitter is solved, and the normal operation of the equipment is restored.

As an embodiment of the present invention, the performing fault initial positioning on the pressure transmitter based on the trend-related features and combining the history data corresponding to the pressure transmitter to obtain a fault positioning source point includes:

Determining a fault type mode corresponding to the pressure transmitter based on the trend related characteristics and the historical record data corresponding to the pressure transmitter, extracting fault mode matching points in the fault type mode, inquiring a historical high-speed component corresponding to the pressure transmitter based on the fault mode matching points, performing association analysis on the historical high-speed component to obtain a high-speed associated component, and performing initial fault positioning on the high-speed associated component to obtain a fault positioning source point.

The fault type mode is a fault expression form set with typical characteristics, which is summarized based on trend related characteristics and historical record data of the pressure transmitter, comprehensively reflects how operating parameters, signal characteristics and the like of the pressure transmitter change with time when different faults occur, and is abstract summary of various faults, for example, pressure continuous abnormal fluctuation can correspond to a sensor fault mode, signal drift corresponds to a circuit parameter drift fault mode and the like; the fault mode matching point refers to a fault expression form set with typical characteristics, which is summarized based on trend related characteristics and historical record data of the pressure transmitter, and comprehensively reflects how the operation parameters, signal characteristics and the like of the pressure transmitter change with time when different faults occur, and is abstract summary of various faults, for example, pressure continuous abnormal fluctuation can correspond to a sensor fault mode, signal drift corresponds to a circuit parameter drift fault mode and the like, the historical high-incidence component refers to a component with frequent faults or relatively high fault probability in the historical record data of the pressure transmitter, the component is more likely to cause problems than other components, such as a pressure sensor membrane, a certain capacitance resistance in a signal conditioning circuit and the like, the high-incidence component refers to other components which are obtained by carrying out association analysis on the historical high-incidence component and are closely related to the function, physical connection or signal transmission on the historical high-incidence component, when the historical high-incidence component fails, the probability of the high-incidence component is increased due to influence of the occurrence of faults, for example, the high-incidence component is a certain capacitance component in the signal conditioning circuit, the operational amplifier connected with the high-power correlation component.

The method comprises the steps of determining a fault type mode corresponding to a pressure transmitter, wherein the fault type mode corresponding to the pressure transmitter can be achieved through a mode identification method, for example, trend related features and historical record data are used as input and are compared with a pre-defined fault type template to find out the most matched fault type, the fault mode matching point in the fault type mode can be achieved through a threshold setting method, for example, according to historical data and experience, a threshold is set for key features in the fault type mode, when feature values exceed or fall below the threshold, the key features are used as fault mode matching points, the historical high-incidence components corresponding to the pressure transmitter are inquired, for example, statistics is conducted on the occurrence times of faults of all components in the historical record data, the components with higher frequency are found out to serve as the historical high-incidence components, association analysis can be conducted on the historical high-incidence components, for example, the components of the pressure transmitter are regarded as network nodes, the connection relations between the components are regarded as edges, the components closely connected with the historical high-incidence components are found out through the network analysis method, the high-incidence components are regarded as the high-incidence components, the fault position of the high-incidence components can be observed, and the fault position of the fault is detected, and the fault is accordingly, the fault is detected, and the fault is detected.

The method and the device help to quickly know the key position of the fault by identifying the core fault type corresponding to the fault positioning source point, thereby pertinently formulating a repair strategy to avoid blind investigation, simultaneously, defining the core fault type and quickly allocating proper repair resources according to past experience, and greatly improving the fault solving efficiency.

The core fault type refers to a fault type which is the main and root cause of the normal operation of the pressure transmitter and corresponds to the pressure sensor, such as damage to a signal transmission line, faults of a circuit control module and the like, when the pressure transmitter breaks down, from various fault expressions and reasons which are easy to occur, the fault type which is the most critical and remarkable in the influence on the operation of equipment is summarized, and optionally, the core fault type which corresponds to the fault location source point can be realized through a decision tree algorithm, such as taking various characteristics (characteristics of pressure, temperature, output signals and the like) of the fault location source point as input, constructing a decision tree model, and gradually determining the core fault type through judgment of the characteristics by the decision tree model.

Further, the method and the device calculate the fault intensity index corresponding to the fault location source point based on the core fault type, can intuitively reflect the influence degree of the fault location source point on the pressure transmitter, help follow-up rapid judgment of the fault priority, reasonably arrange maintenance resources, and treat serious faults preferentially, and efficiently ensure stable operation of equipment.

The fault intensity index is a comprehensive quantization index and is used for measuring the fault severity degree corresponding to a fault positioning source point based on the core fault type.

As one embodiment of the present invention, the calculating, based on the core fault type, a fault intensity index corresponding to the fault location source point includes:

;

In detail, the factor weight refers to the relative importance degree of the ith fault factor when calculating the fault intensity index, for example, for a pressure transmitter, if the performance of the sensor is reduced to greatly affect the normal operation of the equipment, the weight of the fault factor, i.e. the sensor performance, is relatively high, the actual measurement value refers to a real-time value obtained by various monitoring means (such as sensor measurement and data acquisition) during the operation of the equipment for the ith fault factor, for example, if the fault factor is the operation temperature of the equipment, the actual measurement value refers to the current temperature value of the equipment, measured in real time by a temperature sensor, the normal reference value refers to a standard value or a value range of the ith fault factor in a normal and non-fault operation state of the equipment, the maximum fluctuation allowable value refers to a maximum deviation range of the actual measurement value relative to the normal reference value when the equipment is in normal operation, the actual measurement value is a threshold value determined according to the design performance, the working environment and other factors of the equipment, the time period refers to a continuous time period of the equipment fault factor is the running temperature of the equipment, the actual measurement value refers to a function of the equipment, the fault period is set to the performance of the equipment, the fault performance of the equipment is affected by the equipment, and the function is set to the performance of the fault condition, and the function is changed according to the time of the time, and the function of the influence of the fault condition is generated on the performance of the fault condition or the fault condition.

S3, defining a fault high-risk area corresponding to the internal circuit of the pressure transmitter and the sensing unit based on the fault intensity index, performing signal zero calibration on output signals in the high-risk area to obtain calibration output signals, performing performance real-time detection on the calibration output signals to obtain a response performance curve, and determining a key maintenance area corresponding to the pressure transmitter based on the response performance curve.

The invention defines the high-risk fault region corresponding to the internal circuit and the sensing unit of the pressure transmitter based on the fault intensity index, can accurately position the internal problem region of the pressure transmitter, is favorable for rapidly focusing and checking key points, improves the overhaul efficiency, avoids blindness of comprehensive investigation, can perform preventive maintenance on the high-risk region in advance, reduces the probability of sudden faults, and ensures the stable and reliable operation of the pressure transmitter.

The internal circuit is a system composed of various electronic elements (such as resistors, capacitors, transistors, integrated circuits and the like) and circuits, is responsible for processing signals transmitted by a sensing unit, can amplify, filter, convert and the like the weak original signals into standard signals (such as 4-20mA current signals, 0-5V voltage signals and the like) which can be recognized and processed by subsequent equipment, and also bears functions of power management, self diagnosis and the like, and is a key part for realizing signal transmission and control of the pressure transmitter, the sensing unit is one of core components of the pressure transmitter and mainly used for sensing pressure changes, and is usually composed of pressure sensitive elements (such as piezoresistive, capacitive, piezoelectric and the like), and the pressure sensitive elements can convert external pressure physical quantities into electric signals, for example, when the piezoresistive sensitive elements are subjected to pressure, the resistance values of the pressure sensitive elements change, so as to generate electric signal outputs with certain relation with the pressure, thus providing original data for subsequent signal processing and transmission, and the high-risk areas are high-risk candidates and the peripheral electrical connection with the pressure sensors, and the fault areas can be easily and intensively checked and the fault areas are formed in order to detect and maintain the fault areas together.

According to one embodiment of the invention, the method for defining the fault high risk area of the internal circuit of the pressure transmitter corresponding to the sensing unit based on the fault intensity index comprises the steps of analyzing index composition weights corresponding to the fault intensity index, calculating contribution intensity values corresponding to the internal circuit of the pressure transmitter and the sensing unit based on the index composition weights, sorting the internal circuit and the sensing unit based on the contribution intensity values to obtain a sorting result, marking components exceeding a preset threshold value in the sorting result as high risk candidate objects, and defining the fault high risk area corresponding to the pressure transmitter based on the high risk candidate objects.

The index composition weight is a value reflecting the influence degree of different factors on the fault intensity index, the value range is usually between 0 and 1, the sum of all weights is 1, the greater the weight is, the more critical the influence of the factors on the fault intensity index is, the contribution intensity value is calculated according to the index composition weight in combination with the actual situation of fault related factors corresponding to all components in the internal circuit of the pressure transmitter and the sensing unit, the ranking result is a list of all components in the internal circuit of the pressure transmitter and the sensing unit, the contribution intensity value is arranged from large to small (or from small to large according to specific settings), the preset threshold is a standard value set in advance and used for measuring whether the contribution intensity value of the components reaches a higher level, when the contribution intensity value of the components exceeds the threshold, the higher candidate image is considered to have higher fault risk, the contribution intensity value exceeds the preset threshold in the ranking result, the pressure transmitter and the components can be considered to have higher risk of being focused on the current components and the following the primary fault condition.

Further, the analysis of the index composition weight corresponding to the failure strength index can be achieved through a hierarchical structure model, for example, a judgment matrix is constructed by taking factors affecting the failure strength as a criterion layer, such as temperature, humidity and pressure, and the weight of each factor is calculated through expert scoring and other modes, the calculation of the contribution strength value corresponding to the internal circuit of the pressure transmitter and the sensing unit can be achieved through a weighted average method, for example, the calculation of the contribution strength value can be achieved through a weighted average method according to the weight of each factor and the value of each component under the corresponding factors, for example, the sorting process of the internal circuit and the sensing unit can be achieved through a bubble sorting algorithm, for example, two adjacent elements are sequentially compared, if the sequence (such as from big to small and first letter from A to Z) is wrong, the elements are finally exchanged, the sorting result is finally obtained, the components exceeding a preset threshold value in the sorting result are high risk candidate objects through a threshold value comparison method, for example, the assumption that the threshold value is 75 is used, the components exceeding the preset threshold value can be achieved through a circulating statement, the MAB, the corresponding strength value after the components are used in the MAT, the MAT can be seen as the high risk candidate objects are searched for the corresponding to the high risk candidate elements, the high risk candidate elements are connected through the electrical nodes, the map, the high risk transducer is connected with the corresponding to the high risk transducer element is connected through the high risk transducer region, and the high risk transducer element is connected to the corresponding to the risk transducer element region.

According to the invention, the output signal in the high risk area is calibrated by performing signal zero point calibration, so that the calibrated output signal is more accurate, the real and reliable pressure data fed back by the pressure transmitter can be ensured, an accurate basis is provided for subsequent industrial control and monitoring systems based on the data, and erroneous decision and abnormal operation of equipment caused by signal deviation are avoided.

The calibration output signal is a more accurate and reliable signal obtained after zero calibration is performed on the output signal of the high risk area, and the zero offset possibly existing in the original signal is corrected, so that the signal value can accurately reflect the actual pressure measured by the pressure transmitter, a solid foundation is provided for accurate control and accurate data analysis of a subsequent system, and stable operation of the pressure transmitter and related systems is ensured.

Furthermore, the performance of the calibration output signal is detected in real time to obtain a response performance curve, key performance indexes such as response speed and stability of the signal can be rapidly and insignificantly obtained, potential abnormalities can be conveniently found in time, a powerful basis is provided for continuously optimizing the performance of the pressure transmitter, guaranteeing the accuracy and reliability of measured data, and the overall operation efficiency of equipment is improved.

The response performance curve is a curve drawn by taking time as a horizontal axis and taking key performance parameters (such as amplitude, frequency, phase and the like) of a calibration output signal as a vertical axis, for example, when pressure changes, the response performance curve can clearly see how the output signal is pushed to remove tracking pressure changes along with time, including the rising or falling rate of the signal, the duration required for reaching a stable state, whether fluctuation exists in the process and the like, and optionally, the performance real-time detection of the calibration output signal can be realized through a time domain analysis method, for example, when a step is input to a pressure transmitter, the time required for the calibration output signal to rise from an initial value to a final value by a certain proportion (such as 90%) is recorded, namely, the rising time, and the response characteristic of the signal in the time domain is drawn through a plurality of time parameters, thereby constructing the response performance curve.

Furthermore, the key maintenance area corresponding to the pressure transmitter is determined based on the response performance curve, the curve can accurately position the performance abnormal area, blind comprehensive maintenance is avoided, labor and time cost are saved, intervention on the key area which is easy to cause problems can be performed in advance, the fault occurrence probability is reduced, the service life of equipment is prolonged, and stable operation of the equipment is ensured.

The key maintenance area refers to a part closely related to the fault triggering module around the periphery of the fault triggering module, which not only comprises the module directly failed, but also covers other components or areas closely related to the module in the aspects of electrical connection, signal transmission, physical structure and the like.

The method comprises the steps of identifying an abnormal fluctuation section in the response performance curve, marking a key time stamp corresponding to the abnormal fluctuation section, backtracking an operation log corresponding to the pressure transmitter based on the key time stamp, inquiring an abnormal event record in the operation log, positioning a fault triggering module corresponding to the pressure transmitter based on the abnormal event record, and determining the key maintenance area corresponding to the pressure transmitter based on the fault triggering module.

The abnormal fluctuation section refers to a curve part which deviates from a normal fluctuation range in a response performance curve and presents obvious irregularity or larger difference from historical data and theory expected, the fluctuation can be represented as abrupt increase or decrease of signal amplitude, abnormal change of fluctuation frequency and the like, the key timestamp refers to a time mark point corresponding to the abnormal fluctuation section, the time mark point accurately records time with representative characteristics (such as peak value and valley value occurrence moment) in the starting, ending or fluctuation process of the abnormal fluctuation, the operation log refers to a series of information sets automatically recorded or manually recorded by the pressure transmitter in the operation process, the operation log is used for recording operation parameters of equipment at different time points, such as pressure measurement values, output signal intensity, working voltage, current and the like in detail, the equipment starting time and the stopping time are also included, the abnormal event record refers to record content of abnormal conditions of the pressure transmitter in the operation log, the record describes time (corresponding to the key timestamp) of the abnormal occurrence, the abnormal phenomena (such as output signal interruption, measurement pressure value and actual deviation and the like) and the abnormal phenomena are recorded, the abnormal events can be accurately triggered by the electromagnetic event module, if the abnormal event is used for triggering the abnormal module, the abnormal module is used for triggering the abnormal module to perform the function, the abnormal module is used for triggering the abnormal signal, the abnormal module is used for accurately analyzing the abnormal signal, and the abnormal module is used for triggering the abnormal module to have the function, and the abnormal module is well, and the abnormal module is used for the function, and the abnormal module is well has the function-triggering the function, and the abnormal module is caused by the abnormal module and the abnormal module is caused by the abnormal fault and the fault and has the fault and the fault module is caused, causing abnormal fluctuation of the output signal, and the modules causing faults are fault triggering modules.

Further, the identification of the abnormal fluctuation segment in the response performance curve can be achieved through a threshold-based detection method, such as setting a threshold value of a normal fluctuation range, when curve data exceeds the threshold value range, the identification of the abnormal fluctuation segment can be considered as the abnormal fluctuation segment, the marking of the key time stamp corresponding to the abnormal fluctuation segment can be achieved through a traversing method, such as traversing sequentially from the starting point of the identified abnormal fluctuation segment according to a data sequence, recording the time corresponding to each abnormal point as the key time stamp, the backtracking of the operation log corresponding to the pressure transmitter can be achieved through a binary search algorithm, such as for the operation log which is stored in order, the binary search algorithm can be utilized to quickly locate the approximate position of the key time stamp and then obtain the complete operation log record, such as utilizing a regular expression matching algorithm to define the abnormal event pattern in the operation log text, finding out the abnormal event record conforming to the pattern, the fault trigger module corresponding to the pressure transmitter can be achieved through a fault tree analysis method, such as the fault trigger module is constructed by searching the corresponding to the pressure transmitter from the top-level fault trigger module, such as the corresponding to the pressure transmitter is connected with the corresponding to the fault trigger module, and the fault trigger region is established by the fault trigger module, the module and the area corresponding to the node in a certain search depth are key maintenance areas.

S4, inquiring part aging data in the key maintenance area, analyzing a key failure mode corresponding to the key maintenance area according to the part aging data, extracting maintenance monitoring points in the key failure mode, and calculating a health state index corresponding to the key maintenance area based on the maintenance monitoring points.

The invention can assist in judging the residual service life of the parts by inquiring the aging data of the parts in the key maintenance area, plan and replace in advance, prevent faults caused by sudden aging and damage of the parts, analyze the aging rule of the parts according to the aging data, and provide powerful support for optimizing the equipment maintenance strategy and improving the overall operation reliability.

The component aging data refers to a series of data indexes capable of quantitatively representing the aging degree of the component, wherein the data indexes comprise accumulated operation time length of the component, the aging degree is higher as the operation time length is longer, the change condition of key performance parameters such as abrasion degree, accuracy decline value, electrical performance decline index and the like is common, the occurrence frequency of faults is increased along with aging, and the occurrence frequency of the faults of the component is increased.

The method comprises the steps of identifying unique identification codes corresponding to parts in the key maintenance area, calling basic information files corresponding to the parts in the key maintenance area based on the unique identification codes, extracting past maintenance records in the basic information files, and inquiring the parts aging data in the key maintenance area based on the past maintenance records.

The unique identification code refers to a unique identification code given to each part in an important maintenance area, the code is like an identification card number of the part, and can be in the form of numbers, letters or a combination of the numbers and letters, the unique identification code runs through the whole life cycle of the part from production, installation and use maintenance, the basic information file refers to a comprehensive information set of the part in the important maintenance area, the comprehensive information set contains detailed technical parameters of the part, such as model numbers, specifications, materials, rated working conditions and the like, which determine the performance and the applicable scene of the part, the unique identification code also comprises manufacturers, production dates, purchase information and the like of the part, the source and supply chain conditions of the part are helpful to be known, the past maintenance record refers to the record of various maintenance activity information received by the part in the use process, the time of each maintenance is included, the specific content of the detailed description maintenance is, such as whether the operation of cleaning, calibration, part replacement and the like is performed, the maintenance reasons, such as failure maintenance, regular maintenance and the like are recorded, and the operation state feedback of the part after the maintenance is also recorded.

The method comprises the steps of acquiring a two-dimensional code image of a component by a camera, preprocessing the image (such as graying, noise reduction and binarization) by the aid of an open source computer visual library such as OpenCV, then extracting and decoding features, and identifying the unique identification code in the two-dimensional code, wherein the step of extracting a basic information file corresponding to the component in the key maintenance area can be achieved through a hash lookup algorithm, for example, in some NoSQL databases based on hash table structures, the basic information file can be rapidly acquired according to the component code by the aid of the corresponding hash lookup algorithm, the step of extracting the past maintenance record in the basic information file can be achieved through a JSON analysis algorithm (if the basic information file is stored in a JSON format), for example, analyzing the past maintenance record information into a Python dictionary according to the key value pair relation of the dictionary, the step of inquiring the past maintenance record information in the key maintenance area can be achieved through a neural network algorithm, for example, the step of building a database based on Python TensorFlow, and the final model data can be accurately trained, and the final model aging degree of the component can be obtained.

According to the aging data of the components, the key failure modes corresponding to the key maintenance areas are analyzed, the maintenance monitoring points in the key failure modes are extracted, the potential fault risk of the equipment is predicted in advance, the maintenance monitoring points in the key failure modes are extracted, so that maintenance work is more targeted, key parts are monitored by centralized resources, problems are found and solved in time, and the equipment fault rate is effectively reduced.

The key failure mode is a failure mode which is mainly and most affected by the loss of a specified function of equipment or a system and is generalized based on component aging data in a key maintenance area of the pressure transmitter, for example, for a sensing unit of the pressure transmitter, the key failure mode may be a failure mode of aging and cracking of a sensor diaphragm so as to cause inaccurate pressure measurement, or a signal transmission interruption is caused by aging and desoldering of a welding spot of an internal circuit due to long-term expansion and contraction, the maintenance monitoring point is a specific position or parameter which is determined from the key failure mode and is used for monitoring the running state of the equipment in real time and evaluating the health degree of the equipment, for example, in the key failure mode of aging and cracking of the sensor diaphragm, the pressure deformation degree of the diaphragm and the tiny current change of a peripheral circuit can be used as maintenance monitoring points, for the failure mode of the desoldering, and the temperature and the resistance value of the welding spot can be used as maintenance points, alternatively, the key failure mode corresponding to analyze the key failure mode of the key maintenance area can be realized through an FMEA system, for example, the possible failure mode of analyzing the part can be possibly appear through the failure mode of the system is analyzed, the key failure mode determined through the key maintenance area, the key failure mode and the key failure mode corresponding to the failure mode can be extracted from the corresponding failure mode can be extracted through the monitoring point, the failure mode can be extracted by the key failure mode, and the failure mode can be extracted by the corresponding failure mode or the failure mode.

Based on the maintenance monitoring points, the health state indexes corresponding to the key maintenance areas are calculated, so that the health degree of the equipment can be mastered intuitively, potential risks can be positioned quickly, the maintenance strategy can be planned in advance, resources can be allocated reasonably, faults can be prevented effectively, and stable and efficient operation of the equipment can be guaranteed.

The health state index is a quantitative numerical index for comprehensively evaluating the overall health condition of the key maintenance area, wherein the higher the numerical index is, the better the health state of the key maintenance area is, the lower the possibility of faults or performance degradation is, the lower the numerical index is, the worse the health state is, and more close attention is required or maintenance measures are taken.

As an embodiment of the present invention, the calculating, based on the maintenance monitoring point, a health state index corresponding to the key maintenance area includes:

;

In detail, the state coefficient is a coefficient with a value ranging from 0 to 1 for each maintenance monitoring point, and is used for reflecting the actual state of the first maintenance monitoring point; the maintenance weight refers to a weight value which also corresponds to each maintenance monitoring point and is a value between 0 and 1, the weight value reflects the relative importance of a first maintenance monitoring point in evaluating the health state of an important maintenance area, the key component refers to a component which plays a key role in the normal operation and performance of a system in the important maintenance area, such as a mechanical device, an engine, a transmission device and the like, the key component belongs to a core processor, a power supply module and the like in electronic equipment, the performance degradation index refers to an index for measuring the degradation degree of the performance of a first key component relative to an initial state or an ideal state, the index can be a change value of various physical quantities or parameters, such as the abrasion amount of the mechanical component, the signal attenuation degree of the electronic component, the running efficiency reduction proportion of the equipment and the like, the external environment factor refers to various factors which can have an influence on the health state of the equipment or the system in the external environment of the important maintenance area, such as high-temperature environment can accelerate the aging of the electronic component, high-humidity can cause the corrosion of the metal component, the rust of the connection index can cause the metal component, the rust index refers to the total vibration factor k represents the total length of the important maintenance area, the index is a change value between the total maintenance area and the important maintenance area, the index is a total length of the index is 0, the total maintenance factor is represented by the total maintenance factor is the total maintenance area is 1, the method reflects the accumulated influence of various factors on the health state of the key maintenance area in a longer period, wherein the state influence function is a function changing along with time, the influence of temperature factors on the state of the key maintenance area is specially described, the temperature is an environmental factor with great influence on the performance of equipment and a system, and different temperature change conditions can influence the components in the key maintenance area to different degrees.

S5, generating an evaluation index set corresponding to the pressure transmitter based on the health state index, inquiring an index degradation trend corresponding to the evaluation index set, identifying multi-factor coupling weights corresponding to the index degradation trend, and generating a fault monitoring report corresponding to the full life cycle of the pressure transmitter based on the multi-factor coupling weights.

According to the invention, based on the health state index, the evaluation index set corresponding to the pressure transmitter is generated, the running condition of the pressure transmitter can be comprehensively and quantitatively evaluated, potential problems can be rapidly positioned, a scientific basis is provided for maintenance decision, maintenance resources are reasonably distributed, maintenance efficiency is improved, fault risk is reduced, and stable and reliable running of the pressure transmitter is ensured.

The evaluation index set refers to a comprehensive index set, and comprises a series of indexes for evaluating the performance and the state of the pressure transmitter, which are generated based on state level indexes and other related factors, wherein the indexes cover various aspects of reliability, stability, precision, fault risk and the like of the pressure transmitter.

The method comprises the steps of dividing a state operation interval corresponding to the health state index, extracting historical fault characteristics in the state operation interval, constructing a state mapping table corresponding to the historical fault characteristics, carrying out hierarchical distribution on the state mapping table to obtain a state hierarchical index, and generating the evaluation index set corresponding to the pressure transmitter based on the state hierarchical index.

The state operation interval refers to different intervals divided according to the numerical range of the health state index. The state mapping table refers to a table which correspondingly associates a state operation section with a historical fault characteristic, each state operation section corresponds to one or more groups of historical fault characteristics, the possible fault characteristic condition can be quickly known when the pressure transmitter is in a certain state operation section through the mapping relation, the state hierarchy index refers to an index obtained after the state mapping is subjected to hierarchical treatment, and the state mapping table is classified according to a certain logic and rule, and the state hierarchy index is classified according to the content of the state mapping table, the severity of the fault, the probability of occurrence and the like, so that the fault characteristic is classified according to the certain logic and rule.

The method comprises the steps of dividing a state operation interval corresponding to the health state index into a plurality of state operation intervals, wherein the state operation interval can be realized through a statistical analysis method, such as collecting health state index data of a large number of pressure transmitters, calculating statistics such as mean value and standard deviation of the data, dividing the intervals according to the statistics, extracting historical fault characteristics in the state operation interval can be realized through a data retrieval method, such as in a historical fault database, according to the divided state operation interval, retrieving relevant data when faults occur in the corresponding interval, extracting the characteristics from the relevant data to obtain the historical fault characteristics, constructing a state mapping table corresponding to the historical fault characteristics can be realized through an unsupervised classification algorithm, such as clustering the historical fault characteristics, mapping a clustering result with the state operation interval to obtain a state mapping table, hierarchical distribution of the state mapping table can be realized through a hierarchical analysis method, such as through constructing a judgment matrix, determining relative importance of the historical fault characteristics in different state operation intervals, and accordingly obtaining a state hierarchical index, and generating an evaluation index set corresponding to the pressure transmitter can be realized through comprehensive precision index, such as generating a comprehensive precision evaluation index set of the state and the relevant state index and the pressure transmitter.

According to the invention, the index degradation trend corresponding to the evaluation index set is inquired, the multi-factor coupling weight corresponding to the index degradation trend is identified, the action degree of each influence factor can be clarified, the power-assisted maintainer accurately focuses on key factors, resources are reasonably allocated, a more targeted maintenance strategy is formulated, and the stable operation of the pressure transmitter is effectively ensured.

The index degradation trend refers to the trend and situation that the performance of each evaluation index of the pressure transmitter gradually becomes worse along with the change of factors such as the time of use or the number of times of use, for example, the measurement precision index gradually decreases along with the increase of the time of use, the deviation of a measured value and a true value is larger and larger, the stability index is subject to fluctuation aggravation and the like, the multi-factor coupling weight refers to the relative importance degree of each factor on the index degradation under the conditions that a plurality of factors influencing the index degradation of the pressure transmitter interact and influence each other, for example, the factors such as the environmental temperature, the humidity, the pressure fluctuation, the wear of the equipment and the like can influence the performance of the pressure transmitter, the weight value of each factor in the index degradation process is calculated through a certain method, the importance of the factor is represented by the weight value, alternatively, the index degradation corresponding to the query of the evaluation index set can be realized through an ARIMA algorithm, for example, the time sequence data is regarded as a random process, the change of the history data is determined through the interaction and prediction, the entropy coupling weight can be realized through the entropy coupling weight, the entropy weight can be calculated through the entropy weight, and the entropy weight is analyzed by the entropy weight is realized, and the entropy weight is obtained by the entropy weight.

Furthermore, the fault monitoring report corresponding to the whole life cycle of the pressure transmitter is generated based on the multi-factor coupling weight, so that the fault high-speed link can be accurately positioned. According to the influence degree of each factor, the fault risk of different stages is visually presented, the monitoring is enhanced at key nodes, the fault prevention efficiency is greatly improved, and the stable operation of the pressure transmitter is ensured.

The fault monitoring report refers to a comprehensive and detailed document, and integrates key information such as multi-factor coupling weights and the like to comb the running states of the equipment at different stages according to fault related conditions in the whole life cycle of the focusing pressure transmitter. The report not only covers the fault history record of each component of the pressure transmitter, but also predicts the type, time and position of possible faults in the future by combining with the weight of each influencing factor, visually presents the whole health condition of the equipment in the forms of a data chart, text analysis and the like, and provides powerful basis for operation and maintenance decision, and optionally, the generation of the fault monitoring report corresponding to the whole life cycle of the pressure transmitter can be realized through visual tools, such as Tableau, powerBI tools.

Example 2 a functional block diagram of a computer aided pressure transmitter fault diagnosis system of the present invention is shown in figure 2.

The computer-aided pressure transmitter fault diagnosis system 200 of the present invention may be installed in an electronic device. Depending on the functions implemented, the computer-aided pressure transmitter fault diagnosis system may include a feature extraction module 201, an index calculation module 202, a zone determination module 203, a status index module 204, and a report generation module 205. The module of the invention, which may also be referred to as a unit, refers to a series of computer program segments, which are stored in the memory of the electronic device, capable of being executed by the processor of the electronic device and of performing a fixed function.

In the embodiment of the present invention, the functions of each module/unit are as follows:

The feature extraction module 201 is configured to obtain real-time sensing data of the pressure transmitter during operation, analyze dynamic parameter features corresponding to the real-time sensing data, construct a multidimensional parameter matrix of the pressure transmitter in an operation state based on the dynamic parameter features, and extract trend related features in the multidimensional parameter matrix;

The index calculation module 202 is configured to perform initial fault location on the pressure transmitter based on the trend-related features in combination with the historical record data corresponding to the pressure transmitter, obtain a fault location source point, identify a core fault type corresponding to the fault location source point, and calculate a fault intensity index corresponding to the fault location source point based on the core fault type;

The region determining module 203 is configured to define a fault high-risk region corresponding to the internal circuit and the sensing unit of the pressure transmitter based on the fault intensity index, perform signal zero calibration on an output signal in the high-risk region to obtain a calibrated output signal, perform performance real-time detection on the calibrated output signal to obtain a response performance curve, and determine a key maintenance region corresponding to the pressure transmitter based on the response performance curve;

The state index module 204 is configured to query component aging data in the key maintenance area, analyze a key failure mode corresponding to the key maintenance area according to the component aging data, extract a maintenance monitoring point in the key failure mode, and calculate a health state index corresponding to the key maintenance area based on the maintenance monitoring point;

The report generating module 205 is configured to generate an evaluation index set corresponding to the pressure transmitter based on the health status index, query an index degradation trend corresponding to the evaluation index set, identify a multi-factor coupling weight corresponding to the index degradation trend, and generate a fault monitoring report corresponding to a full life cycle of the pressure transmitter based on the multi-factor coupling weight.

In detail, the modules in the computer-aided pressure transmitter fault diagnosis system 200 in the embodiment of the present invention use the same technical means as the above-mentioned computer-aided pressure transmitter fault diagnosis method in fig. 1, and can produce the same technical effects, and are not described herein.

It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential characteristics thereof.

Finally, it should be noted that the above-mentioned embodiments are merely for illustrating the technical solution of the present invention and not for limiting the same, and although the present invention has been described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications and equivalents may be made to the technical solution of the present invention without departing from the spirit and scope of the technical solution of the present invention.

Claims

1. A computer-aided pressure transmitter fault diagnosis method, characterized in that the method comprises:

Acquire real-time sensor data of the pressure transmitter during operation, analyze dynamic parameter features corresponding to the real-time sensor data, construct a multi-dimensional parameter matrix of the pressure transmitter in operation based on the dynamic parameter features, and extract trend-related features in the multi-dimensional parameter matrix;

Based on the trend-related features and the historical record data corresponding to the pressure transmitter, the pressure transmitter is initially fault-located to obtain a fault location source point, the core fault type corresponding to the fault location source point is identified, and based on the core fault type, the fault intensity index corresponding to the fault location source point is calculated;

Based on the fault intensity index, a high-risk fault area corresponding to the internal circuit and the sensing unit of the pressure transmitter is delineated, a signal zero point calibration is performed on the output signal in the high-risk area to obtain a calibrated output signal, a real-time performance detection is performed on the calibrated output signal to obtain a response performance curve, and based on the response performance curve, a key maintenance area corresponding to the pressure transmitter is determined;

Querying the component aging data in the key maintenance area, analyzing the key failure mode corresponding to the key maintenance area according to the component aging data, extracting the maintenance monitoring points in the key failure mode, and calculating the health status index corresponding to the key maintenance area based on the maintenance monitoring points;

Based on the health status index, an evaluation index set corresponding to the pressure transmitter is generated, the indicator degradation trend corresponding to the evaluation index set is queried, and the multi-factor coupling weight corresponding to the indicator degradation trend is identified; based on the multi-factor coupling weight, a fault monitoring report corresponding to the entire life cycle of the pressure transmitter is generated.

2. The computer-aided pressure transmitter fault diagnosis method according to claim 1, characterized in that the multi-dimensional parameter matrix of the pressure transmitter in the operating state is constructed based on the dynamic parameter characteristics, comprising:

Extracting core variables corresponding to the dynamic parameter features;

Based on the core variables, generating a time sequence of working conditions corresponding to the pressure transmitter;

Perform sliding window segmentation on the working condition time series to obtain window data blocks;

Performing cross-domain fusion on the data in the window data block to obtain a fused data block;

identifying corresponding multi-dimensional attributes of the fused data block;

Based on the multi-dimensional attributes, a multi-dimensional parameter matrix of the pressure transmitter in the operating state is constructed.

3. The computer-aided pressure transmitter fault diagnosis method according to claim 1, characterized in that the initial fault location of the pressure transmitter based on the trend-related features combined with the historical record data corresponding to the pressure transmitter to obtain the fault location source point includes:

Determine a fault type mode corresponding to the pressure transmitter based on the trend-related features combined with historical record data corresponding to the pressure transmitter;

Extracting a fault mode matching point in the fault type mode;

Based on the fault mode matching point, query the historical high-incidence component corresponding to the pressure transmitter;

Performing correlation analysis on the historically high-incidence components to obtain high-incidence correlated components;

Perform preliminary fault location on the frequently associated components to obtain the fault location source point.

4. The computer-aided pressure transmitter fault diagnosis method according to claim 1, wherein the step of calculating the fault intensity index corresponding to the fault location source point based on the core fault type comprises:

The fault intensity index corresponding to the fault location source point is calculated using the following formula:

;'

in, represents the fault intensity index corresponding to the fault location source point, represents the number of fault factors associated with the core fault type, Indicates the quantity index corresponding to the fault factor, Indicates The factor weight corresponding to each fault factor is: represents the actual measured value corresponding to the i-th fault factor, Indicates The normal reference value corresponding to each fault factor is: Indicates The maximum fluctuation allowable value corresponding to each fault factor is: Indicates the monitoring time period, Indicates The failure factor at time The fault impact function.

5. The computer-aided pressure transmitter fault diagnosis method according to claim 1, characterized in that the step of defining the high-risk fault area corresponding to the internal circuit and the sensing unit of the pressure transmitter based on the fault intensity index comprises:

Analyzing the index component weights corresponding to the fault intensity index;

Based on the index component weights, calculating contribution intensity values corresponding to the internal circuit and the sensing unit of the pressure transmitter;

Based on the contribution strength value, the internal circuit and the sensor unit are sorted to obtain a sorting result;

Marking components in the sorting results that exceed a preset threshold as high-risk candidates;

Based on the high-risk candidate objects, a high-risk failure area corresponding to the pressure transmitter is defined.

6. The computer-aided pressure transmitter fault diagnosis method according to claim 1, wherein determining the key maintenance area corresponding to the pressure transmitter based on the response performance curve comprises:

Identifying an abnormal fluctuation segment in the response performance curve;

Marking the key timestamp corresponding to the abnormal fluctuation segment;

Based on the key timestamp, trace back the operation log corresponding to the pressure transmitter;

Query the abnormal event records in the operation log;

Based on the abnormal event record, locate the fault trigger module corresponding to the pressure transmitter;

Based on the fault trigger module, a key maintenance area corresponding to the pressure transmitter is determined.

7. The computer-aided pressure transmitter fault diagnosis method according to claim 1, wherein the querying of the component aging data in the key maintenance area comprises:

Identify the unique identification code corresponding to the components in the key maintenance area;

Based on the unique identification code, retrieve the basic information file corresponding to the component in the key maintenance area;

Extracting past maintenance records from the basic information archive;

Based on the past maintenance records, the component aging data in the key maintenance area is queried.

8. The computer-aided pressure transmitter fault diagnosis method according to claim 1, wherein the step of calculating the health status index corresponding to the key maintenance area based on the maintenance monitoring point comprises:

The health status index corresponding to the key maintenance area is calculated using the following formula:

;

in, Indicates the health status index corresponding to the key maintenance area, Indicates the number of maintenance monitoring points. represents the quantity index corresponding to the maintenance monitoring point, Indicates The state coefficient corresponding to each maintenance monitoring point is: Indicates The maintenance weight corresponding to each maintenance monitoring point is: Indicates the number of key components in the key maintenance area. Indicates the quantity index corresponding to the key components, Indicates The performance degradation indicators corresponding to the key components are: represents the number of external environmental factors in the key maintenance area, Represents the quantitative index of external environmental factors, Indicates The corresponding influence coefficient of each external environmental factor is Indicates the total maintenance time. It represents the influence function of the temperature changing with time on the status of the key maintenance area.

9. The computer-aided pressure transmitter fault diagnosis method according to claim 1, wherein generating an evaluation index set corresponding to the pressure transmitter based on the health status index comprises:

Dividing the state operation interval corresponding to the health state index;

Extracting historical fault features in the state operation interval;

Performing hierarchical allocation on the state mapping table to obtain a state hierarchy index;

Based on the state hierarchy index, an evaluation index set corresponding to the pressure transmitter is generated.

10. A computer-aided pressure transmitter fault diagnosis system, characterized in that the system comprises:

A feature extraction module is used to obtain real-time sensor data of the pressure transmitter during operation, analyze dynamic parameter features corresponding to the real-time sensor data, construct a multi-dimensional parameter matrix of the pressure transmitter in operation based on the dynamic parameter features, and extract trend-related features in the multi-dimensional parameter matrix;

An index calculation module, used to perform preliminary fault location on the pressure transmitter based on the trend-related features combined with the historical record data corresponding to the pressure transmitter, obtain a fault location source point, identify a core fault type corresponding to the fault location source point, and calculate a fault intensity index corresponding to the fault location source point based on the core fault type;

an area determination module, for delineating a high-risk area of faults corresponding to the internal circuit and the sensing unit of the pressure transmitter based on the fault intensity index, performing a signal zero point calibration on the output signal in the high-risk area to obtain a calibrated output signal, performing a real-time performance detection on the calibrated output signal to obtain a response performance curve, and determining a key maintenance area corresponding to the pressure transmitter based on the response performance curve;

A state index module, used to query the component aging data in the key maintenance area, analyze the key failure mode corresponding to the key maintenance area according to the component aging data, extract the maintenance monitoring points in the key failure mode, and calculate the health state index corresponding to the key maintenance area based on the maintenance monitoring points;

A report generation module is used to generate an evaluation index set corresponding to the pressure transmitter based on the health status index, query the indicator degradation trend corresponding to the evaluation index set, and identify the multi-factor coupling weight corresponding to the indicator degradation trend, and generate a fault monitoring report corresponding to the entire life cycle of the pressure transmitter based on the multi-factor coupling weight.