CN120142382B - Electric melting sleeve connection monitoring method for polyurethane direct-buried heat preservation pipe - Google Patents
Electric melting sleeve connection monitoring method for polyurethane direct-buried heat preservation pipe Download PDFInfo
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Abstract
本发明公开了一种聚氨酯直埋保温管的电热熔套连接监测方法，属于电热熔套安装监测技术领域，具体包括：在电热熔套两侧环形接触面嵌入分布式电极组，与聚氨酯保温层内导电增强结构形成电耦合网络；在通电加热时，向电极组施加动态调制、覆盖熔融界面介电弛豫频段的宽频交变电流信号；实时采集电极对电压响应信号，解算出含实部和虚部阻抗分量的复数阻抗谱；分析实部阻抗非线性衰减特征，若不符规律则预警；解析虚部阻抗相位角波动规律，提取介电异常特征，与预设模型匹配，超容差范围则预警；最后，基于电极组阻抗响应定位熔融缺陷的空间分布。
The invention discloses a method for monitoring the connection of an electric hot melt sleeve of a polyurethane direct-buried thermal insulation pipe, which belongs to the technical field of electric hot melt sleeve installation monitoring, and specifically comprises: embedding a distributed electrode group into the annular contact surfaces on both sides of the electric hot melt sleeve to form an electric coupling network with a conductive reinforcement structure in a polyurethane thermal insulation layer; applying a broadband alternating current signal that is dynamically modulated and covers the dielectric relaxation frequency band of a molten interface to the electrode group when power is turned on for heating; collecting the voltage response signal of the electrode pair in real time, and solving the complex impedance spectrum containing real and imaginary impedance components; analyzing the nonlinear attenuation characteristics of the real impedance, and issuing an early warning if it does not conform to the law; analyzing the fluctuation law of the imaginary impedance phase angle, extracting dielectric abnormal characteristics, matching them with a preset model, and issuing an early warning if the tolerance range is exceeded; finally, locating the spatial distribution of the melting defect based on the impedance response of the electrode group.
Description
Technical Field
The invention relates to the technical field of installation monitoring of electric melting sleeves, in particular to a method for monitoring connection of an electric melting sleeve of a polyurethane direct-buried heat-insulating pipe.
Background
In the field of energy transportation, the polyurethane directly buried heat insulation pipe is widely applied to a plurality of systems such as central heating, cooling, oil transportation and the like by virtue of good heat insulation performance, corrosion resistance and long service life. The sealing performance and reliability requirements of the system on the pipeline connection are extremely high, and once the pipeline connection part is in a problem, a large amount of energy waste can be caused, and safety accidents can be caused to influence the normal operation of the whole conveying system. Therefore, ensuring the connection quality of the polyurethane direct-buried insulation pipe is important. The electric melting sleeve connection is used as a common connection mode, and the monitoring of the connection quality becomes a key link for guaranteeing the stable operation of a pipeline system.
At present, some researches and practices are carried out on the monitoring of the connection quality of the polyurethane direct-buried insulating pipe electric melting sleeve. The connection quality is evaluated by detecting the change of the conductivity, the current and the voltage are measured by arranging electrodes at the connection part, the conductivity is calculated, and whether the connection is good or not is judged according to the change of the conductivity. Still other ultrasonic flaw detection methods detect the presence of defects at the joint by emitting ultrasonic waves and analyzing the characteristics of the reflected waves. In addition, there is also a monitoring method based on the change of resistance, which evaluates the connection state by monitoring the real-time change of the resistance of the connection part.
However, there are a number of disadvantages to these existing monitoring methods. On the one hand, the real-time performance is poor. Most of the methods are to detect after connection, so that the connection state is difficult to grasp in real time in the heating and melting process of the electric melting sleeve, and once a problem is found, irreversible loss is often caused. On the other hand, the detection accuracy is limited. For some microscopic defects, such as micro bubbles, impurities, etc., it is difficult to accurately detect, and these microscopic defects may gradually expand with time, affecting the long-term service performance of the pipeline. And the space positioning capability is insufficient, and the specific space position of the defect at the connecting part is difficult to accurately determine, so that the follow-up repair work is lack of pertinence and low in efficiency.
Disclosure of Invention
The invention aims to provide a method for monitoring connection of an electric melting sleeve of a polyurethane direct-buried heat-insulating pipe, which solves the following technical problems:
The existing electric melting sleeve monitoring method is poor in real-time performance and difficult to locate some microscopic defects.
The aim of the invention can be achieved by the following technical scheme:
A method for monitoring connection of an electric melting sleeve of a polyurethane direct-buried heat-insulating pipe comprises the following steps:
embedding distributed electrode groups in annular contact surfaces at two sides of the electric melting sleeve, wherein the distributed electrode groups and a conductive enhancement structure in the polyurethane heat insulation layer form an electric coupling network;
in the process of electrifying and heating the electric melting sleeve, a dynamically modulated broadband alternating current signal is applied to the electrode group, and the frequency range of the broadband alternating current signal covers the dielectric relaxation frequency band of the melting interface;
Collecting voltage response signals of each electrode pair in the distributed electrode group in real time, and calculating complex impedance spectrums of the electric melting sleeve based on the voltage response signals, wherein the complex impedance spectrums comprise real-part impedance components and imaginary-part impedance components;
analyzing nonlinear attenuation characteristics of the real part impedance component, and generating a fusion defect early warning signal if the nonlinear attenuation characteristics do not accord with an expected rule;
The dielectric abnormal characteristics of the microstructure of the melting interface are extracted by analyzing the fluctuation rule of the phase angle of the imaginary impedance component along with the frequency change, the dielectric abnormal characteristics are matched with a preset melting interface uniformity model, and if the matching result exceeds a preset tolerance range, a melting defect early warning signal is generated;
the spatial distribution of the fusion defect is localized based on the impedance response of the distributed electrode set.
The conductive reinforcing structure is a wire mesh or a carbon fiber array embedded in the polyurethane heat preservation layer, the wire mesh or the carbon fiber array is uniformly distributed along the circumferential direction of the polyurethane heat preservation layer, and is electrically connected with the annular electrode mounting surface of the distributed electrode group in the full circumferential direction through welding or conductive adhesive.
The further scheme of the invention is that the dynamic modulation mode of the broadband alternating current signal comprises the following steps:
marking the time interval of the electrifying and heating of the electric melting sleeve as [ t1, t2], wherein the broadband alternating current signal comprises a low-frequency-band continuous sweep frequency signal and a high-frequency-band pulse modulation signal;
When the frequency range is in the time interval of [ t1, t0], t0 is a preset value, a low-frequency-band continuous sweep frequency signal is applied, and the frequency range of the low frequency band corresponds to the response frequency band of the overall conductivity of the polyurethane material in a molten state;
When the frequency range is in the time interval (t 0, t 2), a high-frequency-band pulse modulation signal is superimposed on the basis of a low-frequency-band continuous sweep frequency signal, wherein the frequency range of the high frequency band corresponds to a local dielectric relaxation frequency band caused by microscopic defects of a melting interface, and the microscopic defects comprise bubbles or impurities;
In the electric heating sleeve electrifying and heating process, impedance response data of the electrode group are collected in real time, the interval size of frequency change in the low-frequency-band continuous sweep frequency signal and the ratio of pulse duration to period in the high-frequency-band pulse modulation signal are adjusted according to the impedance response data, and the broadband alternating current signal is adaptively matched with the melting process of the polyurethane material.
The solution of the complex impedance spectrum specifically comprises the following steps:
Synchronous detection processing is carried out on the voltage response signal, a part which is in the same frequency and phase as the excitation signal in the voltage response signal is separated and marked as a real part voltage component, and a part which is in quadrature with the excitation signal in phase is separated and marked as an imaginary part voltage component;
Calculating the real part impedance through the real part voltage component, obtaining the change rate of the real part impedance in a radial space, constructing a dynamic distribution model of the thickness of the molten layer, calculating the imaginary part impedance based on the imaginary part voltage component, representing the value of the imaginary part impedance in a cloud picture form by taking the spatial position as a coordinate, generating a dielectric characteristic distribution cloud picture, and obtaining the local extreme point of the imaginary part impedance in the cloud picture.
As a further aspect of the invention, the process of extracting dielectric anomaly characteristics of a molten interface microstructure includes:
Performing multi-scale time-frequency analysis on the imaginary impedance component, decomposing the signal of the imaginary impedance component into different frequency components, acquiring fluctuation changes of the different frequency components at different time points, and extracting non-stationary fluctuation components of the phase angle at a specific frequency band;
constructing an energy spectrum according to the extracted non-stationary fluctuation component of the phase angle, wherein the energy spectrum is used for representing energy distribution of phase angle fluctuation under different frequencies, and calculating an integral value of the energy spectrum in a preset defect characteristic frequency band, wherein the integral value represents phase angle fluctuation energy of all frequencies in the frequency band;
the frequency position of a peak value in the energy spectrum is obtained, when a low-frequency energy peak appears in the energy spectrum, the unfused defect is a macroscopic crack defect, and when a high-frequency energy peak appears in the energy spectrum, the unfused defect is a microscopic bubble/impurity defect.
As a further scheme of the invention, the distributed electrode group is arranged in the following way:
In the axial direction of the electric melting sleeve, n groups of annular electrodes are arranged, the detection areas of the adjacent annular electrodes are axially overlapped, each group of annular electrodes comprises m layers of concentric annular electrodes with different radial directions, each layer of annular electrodes comprises o electrode units, the electrode units are distributed on the annular electrodes in a circumferentially symmetrical mode, n, m and o are preset values, each electrode unit is connected with a switching circuit, and different electrode units are combined in different ways through the control of the switching circuits to form a plurality of groups of independent detection loops.
As a further proposal of the invention, the spatial distribution of the positioning fusion defect comprises axial positioning, radial positioning and circumferential positioning, and the positioning process is as follows:
Acquiring impedance response gradient change of an axial overlap detection area, starting axial detection from one end of a melting interface, marking the position as an axial defect starting point when the impedance response gradient at any position is identified to be increased beyond a preset value, continuing to identify along the axial direction until the impedance response gradient at any position is lower than the preset value, marking the position as an axial defect ending point, and obtaining an area between the defect starting point and the defect ending point as an axial positioning area of the defect;
Acquiring impedance responses of concentric ring electrodes of different layers in the axial positioning area, and calculating concentric ring electrode layers where the defects are located according to impedance response differences of the concentric ring electrodes of different radial positions, namely, the radial positioning range of the defects;
and obtaining impedance response generated by each detection loop in the radial positioning range of the axial positioning area, calculating the uniformity degree of the molten layer in the circumferential direction by analyzing impedance response differences of the detection loops, and judging that the corresponding circumferential area has the molten defect if the impedance difference of any adjacent electrode units exceeds a set proportion.
The method for constructing the preset fusion interface uniformity model comprises the following steps of:
Monitoring and data acquisition are carried out on a completely sealed melting interface under standard experimental conditions, and the change condition of real part impedance along with time is recorded under different heating stages and different temperatures to form a real part impedance attenuation curve;
the melting interface uniformity model comprises a relation model of a real part impedance gradient and a melting layer thickness and an imaginary part phase fluctuation mode classification model;
Inputting real part impedance data in an impedance reference database into a convolutional neural network, learning the change characteristics of the real part impedance under different positions and different conditions, establishing a nonlinear mapping relation between the real part impedance gradient and the thickness of a molten layer, and obtaining a relation model of the real part impedance gradient and the thickness of the molten layer;
Inputting imaginary part phase fluctuation template data in an impedance reference database into a support vector machine algorithm, wherein the template data comprises imaginary part phase fluctuation modes corresponding to different defect types, the support vector machine algorithm carries out classification training on the template data, stores imaginary part phase fluctuation characteristics corresponding to different defect types, generates a plurality of phase fingerprint identification libraries, and obtains an imaginary part phase fluctuation mode classification model;
Inputting the real-time monitoring data into a trained fusion interface uniformity model, and outputting a real-part impedance data fusion quality score and defect confidence coefficient parameters of the imaginary part phase data.
The invention further provides a scheme that the method further comprises the following steps:
Based on the axial positioning, radial positioning, circumferential positioning and heating time parameters, a defect three-dimensional evolution model is established, and the defect three-dimensional evolution model comprises the growth rate of the defect volume along with the heating time and the change track of the shape position.
The invention has the beneficial effects that:
the invention adopts the distributed electrode group and the conductive enhancement structure to form a full-circumferential electric coupling network, and combines the dynamic modulation technology of broadband alternating current signals to synchronously collect impedance response data in the heating process of the electric melting sleeve. By analyzing the nonlinear attenuation characteristic of the real impedance and the fluctuation rule of the phase angle of the imaginary part in real time, the interface defect can be directly identified in the melting stage, and the hysteresis limit of the traditional offline detection is broken through.
And decomposing the imaginary impedance component into different frequency components through a multi-scale time-frequency analysis algorithm, and extracting the phase angle fluctuation characteristic of the specific frequency band. The technology can effectively distinguish macroscopic cracks from microscopic bubbles/impurity defects, the detection sensitivity is improved by one order of magnitude compared with that of an ultrasonic flaw detection technology, and the problem of interface non-uniformity which is difficult to find by the traditional method can be captured.
Based on impedance gradient change analysis of the axial overlapping detection area, the accurate positioning of the defects in the three-dimensional space is realized by combining the response difference of the radial concentric electrode layers and the combination detection of the circumferential electrode units. According to the method, the axial distribution range, the radial depth and the circumferential position of the defect can be accurately determined by quantifying impedance response differences of different positions, so that a reliable basis is provided for targeted repair.
According to the electrical characteristic change of the melting process of the polyurethane material, the sweep frequency interval and the pulse duty ratio are dynamically adjusted, so that the excitation signal is always matched with the material state. The technology effectively solves the problem of signal distortion in the traditional fixed frequency detection, and ensures stable monitoring precision in the material phase change process.
Drawings
The invention is further described below with reference to the accompanying drawings.
Fig. 1 is a schematic flow chart of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1, the invention relates to a method for monitoring connection of an electric melting sleeve of a polyurethane direct-buried heat preservation pipe, which comprises the following steps:
Step one, constructing a distributed electrode network:
The multi-layer distributed electrode groups are symmetrically embedded in annular contact surfaces at two sides of the electric melting sleeve, the electrode groups are made of high-temperature resistant conductive materials, and the arrangement density of the electrode groups is optimally designed according to the dielectric characteristics of polyurethane materials. The electrode group and the electric melting sleeve matrix form an integrated structure through a precise injection molding process, so that stable electrical performance is ensured to be maintained in a high-temperature melting process. The distributed electrode group and the conductive enhancement structure (such as a wire mesh or a carbon fiber array) in the polyurethane heat insulation layer are connected in a full circumferential conductive manner to form a three-dimensional electric coupling network, and the network covers the whole melting interface area and provides a low-impedance channel for broadband signal transmission.
Step two, dynamic broadband signal excitation:
In the stage of electrifying and heating the electric melting sleeve, an intelligent signal generator is adopted to apply a dynamically modulated broadband alternating current signal to the electrode group. The signal comprises a low-frequency band continuous sweep frequency signal (10 Hz-100 kHz) and a high-frequency band pulse modulation signal (1 MHz-10 MHz), and the frequency range of the signal covers the full dielectric relaxation frequency band from solid state to molten state of the polyurethane material. The signal modulation strategy adopts double closed-loop control, namely a temperature feedback loop adjusts the signal amplitude in real time according to the heating power, and an impedance feedback loop dynamically optimizes the sweep frequency interval and the pulse duty ratio to ensure the synchronization of the excitation signal and the phase change process of the material.
Step three, multi-dimensional impedance data acquisition:
The voltage response signals of each electrode pair in the distributed electrode group are obtained in real time through the high-precision synchronous acquisition system, and the sampling rate is more than 100 kS/s. The phase-locked amplifying technology is adopted to carry out quadrature decomposition on the voltage signal, and a real part voltage component which is in phase with the same frequency of the excitation signal and an imaginary part voltage component which is in quadrature phase with the excitation signal are separated. And calculating complex impedance values of the corresponding electrode pairs based on ohm's law, and constructing a three-dimensional impedance database containing 2000+ measuring points, so as to provide data support of full space coverage for subsequent analysis.
Step four, real part impedance nonlinear analysis:
And extracting attenuation curve characteristic parameters of the real part impedance by using a polynomial fitting algorithm, wherein the attenuation curve characteristic parameters comprise attenuation rate, inflection point position, curve symmetry and the like. And establishing a nonlinear attenuation model based on support vector regression, wherein the model fuses parameters such as temperature field distribution, material thermal conductivity and the like, and can predict an impedance attenuation track in an ideal state. When the deviation between the actual measurement curve and the prediction model exceeds a set threshold value, triggering a fusion defect early warning mechanism.
Fifthly, extracting imaginary part phase fluctuation characteristics:
The imaginary impedance component is subjected to continuous wavelet transformation to decompose 12 phase fluctuation signals of different frequency bands. And extracting the instantaneous phase of each frequency band signal through Hilbert transformation, and constructing a time-frequency domain joint characteristic matrix. And carrying out pattern recognition on the characteristic matrix by adopting a convolutional neural network, and judging that microscopic defects exist when detecting that the phase fluctuation energy of a specific frequency band (such as 100kHz-500 kHz) exceeds 1.5 times of a reference value.
Step six, three-dimensional space positioning of defects:
and determining the axial distribution range of the defects by adopting a cubic spline interpolation algorithm based on impedance gradient analysis of the axial overlapping electrode group. And inverting the radial depth of the defect by using a Bayesian estimation method through the impedance response difference of the radial layered electrodes. And reconstructing a fused layer thickness distribution cloud chart by utilizing an impedance matrix of the circumferential electrode array and combining a Tikhonov regularization algorithm, and identifying a circumferential uneven region. And finally, generating a defect positioning report containing XYZ three-dimensional coordinates, and providing accurate guidance for subsequent repair.
In a preferred embodiment of the present invention, the conductive reinforcing structure is a wire mesh or a carbon fiber array embedded in the polyurethane insulation layer, and the wire mesh or the carbon fiber array is uniformly distributed along the circumferential direction of the polyurethane insulation layer and is electrically connected with the annular electrode mounting surface of the distributed electrode group in the full circumferential direction through welding or conductive adhesive.
In another preferred embodiment of the present invention, the dynamic modulation mode of the wideband alternating current signal includes:
the time interval of electrifying and heating the electric melting sleeve is set as [ t1, t2]. The broadband alternating current signal consists of a low-frequency band continuous sweep frequency signal and a high-frequency band pulse modulation signal.
And applying a low-frequency band continuous sweep frequency signal in a time interval (t 1, t 0) (t 0 represents a time point when the initial stage of the electric heating of the electric melting sleeve is finished). The low band frequency range, e.g., 10Hz to 100kHz, corresponds to the response band of the overall conductivity of the polyurethane material when in the molten state. In the initial stage of heating, the polyurethane material is changed from a solid state to a molten state, the overall conductivity of the polyurethane material begins to change, and the low-frequency-band continuous sweep frequency signal can effectively detect the change of the overall conductivity. For example, as the material is gradually melted, the internal molecular structure changes to enable free electron movement to be more active, so that the overall conductivity is enhanced, and the low-frequency-band continuous sweep frequency signal can capture the change trend, so that basic data is provided for subsequent monitoring analysis.
When the time interval (t 0, t 2) is entered, the high-frequency pulse modulation signal is superimposed on the low-frequency continuous sweep signal, the high-frequency range, such as 1MHz to 10MHz, in the latter stage of heating, the polyurethane material is further melted, the molten interface may generate microscopic defects, for example, when bubbles exist at a melting interface, the distribution of an electric field around the bubbles changes, so that the local dielectric constant changes, and the high-frequency-band pulse modulation signal can detect the change.
And in the whole process of electrifying and heating the electric melting sleeve, acquiring impedance response data of the electrode group in real time. And dynamically adjusting the low-frequency band continuous sweep frequency signal and the high-frequency band pulse modulation signal according to the data. For low-frequency band continuous sweep signals, if the acquired impedance response data show that the conductivity of the material is slow, the frequency change interval can be properly increased, such as from 1kHz to 2kHz, and if the conductivity is fast, the frequency change interval can be reduced, such as from 1kHz to 0.5kHz. For high-band pulse modulated signals, the ratio of pulse duration to period (duty cycle) is increased, e.g., from 30% to 50%, when microscopic defects are detected as likely, and the duty cycle is suitably decreased, e.g., from 30% to 20%, when no evidence of microscopic defects is evident. Through the dynamic adjustment, the broadband alternating current signal can be adaptively matched with the melting process of the polyurethane material, and the monitoring accuracy and effectiveness are remarkably improved.
In another preferred embodiment of the present invention, the resolving of the complex impedance spectrum specifically includes:
firstly, carrying out synchronous detection processing on voltage response signals acquired in real time. This is achieved by means of a high precision synchronous detection circuit or a related software algorithm. Specifically, the voltage response signal is accurately compared with the excitation signal by a phase-locked loop technique. On the basis, the part of the voltage response signal, which is the same in frequency and phase as the excitation signal, can be accurately distinguished and separated, then the part of the voltage response signal is marked as a real part voltage component, and meanwhile, the part of the voltage response signal, which is orthogonal to the phase of the excitation signal, is also separated by utilizing a phase quadrature detection technology and is marked as an imaginary part voltage component. The accurate separation process lays a solid foundation for subsequent impedance calculation and related characteristic analysis.
Next, calculation of real part impedance is performed based on the separated real part voltage component. According to ohm's law, by combining the known exciting current, the real impedance value can be accurately obtained through a corresponding calculation program. To gain further insight into the molten state, the rate of change of the real impedance in radial space also needs to be obtained. This requires multi-point measurements of the real impedance at different radial positions, for example, measuring points are set at regular intervals (e.g., 0.5 mm) in the radial direction, and the real impedance values at each point are acquired. By analyzing the multi-point data, the change rate of the real part impedance in the radial space is calculated by using a differential algorithm or a curve fitting slope method. According to the change rate data, a model capable of accurately reflecting the dynamic distribution condition of the thickness of the molten layer is constructed by combining physical characteristic parameters and a heat transfer theory of the polyurethane material in the melting process. The model can intuitively show the change condition of the thickness of the molten layer along the radial direction with time in the electrifying and heating process of the electric melting sleeve.
After the real-part impedance correlation processing is completed, calculation work of the imaginary-part impedance is performed based on the imaginary-part voltage component. The imaginary impedance is also calculated by a specially designed algorithm based on ohm's law and excitation current information. In order to more intuitively and comprehensively present the distribution characteristic of the imaginary impedance in space, the value of the imaginary impedance is visually represented in a cloud form by taking the space position as a coordinate and using professional drawing software or self-programming drawing program, so as to generate a dielectric characteristic distribution cloud. In this cloud, different colors or gray values represent different magnitudes of the imaginary impedance values. Through careful observation and analysis of the cloud image, the local extreme point of the imaginary impedance in the cloud image is obtained by using an image recognition algorithm or a manual screening mode. These local extrema often correspond to regions of significant change in dielectric properties at the melt interface, and are of great indicative significance for determining whether microscopic defects are present and for assessing melt quality.
In a preferred case of this embodiment, the process of extracting the dielectric anomaly characteristic of the molten interface microstructure includes:
First, a multi-scale time-frequency analysis is performed for the imaginary impedance component. This process is aided by advanced mathematical tools such as wavelet transform algorithms. By selecting a suitable wavelet basis function, the imaginary impedance component signal is decomposed according to different time scales and frequency scales, thereby decomposing it into a series of different frequency components. In the decomposition process, the fluctuation and change conditions of the different frequency components at different time points in the heating process of the electric melting sleeve are accurately obtained by utilizing a time sliding window technology. Then, a phase angle analysis algorithm is used to focus on a specific frequency band, for example, a frequency band range of 100kHz to 500kHz, which is sensitive to microstructure change, and the non-stationary fluctuation component of the phase angle in the frequency band is carefully extracted. These non-stationary wave components often contain critical information about the microstructure changes of the melt interface, which is the core data for subsequent analysis.
Then, an energy spectrum is constructed from the non-stationary fluctuation component of the extracted phase angle. The energy spectrum is a tool for visually representing the energy distribution of phase angle fluctuations at different frequencies. When the energy spectrum is constructed, phase angle fluctuation signals in a time domain are converted into a frequency domain by using mathematical means such as Fourier transformation, and energy values carried by phase angle fluctuation under different frequencies are calculated according to corresponding energy calculation formulas. By plotting these energy values as a function of frequency, a complete energy spectrum is formed. On the basis, the integral value of the energy spectrum in the preset defect characteristic frequency band is further calculated. The preset defect characteristic frequency band is determined through a plurality of experiments and theoretical analysis, and different types of defects correspond to different frequency band ranges. The integral value represents virtually the sum of the phase angle fluctuation energies of all frequencies in this particular band. By comparing the integrated value with a preset reference energy threshold value, when the integrated value exceeds the reference energy threshold value, the existence of unfused defects on the melting interface can be judged. This is because unfused defects can cause abnormal changes in dielectric properties, resulting in significant changes in phase angle fluctuation energy within a particular frequency band.
Finally, the frequency location of the peak in the energy spectrum is analyzed in depth. When a low-frequency energy peak appears in the energy spectrum, for example, the energy peak appears in the low-frequency range of 1kHz to 10kHz, and according to a large amount of experimental data and experience summary, the corresponding unfused defect is a macroscopic crack defect with high probability. This is because the existence of macro-cracks can have a large range of influence on the electric field distribution, so that the phase angle fluctuation of the low frequency band can be obviously peaked. Whereas when a high frequency energy peak occurs in the energy spectrum, for example, an energy peak occurs in the high frequency band of 1MHz to 10MHz, the unfused defect in this case is typically a microscopic bubble/impurity defect. Microscopic bubbles or impurities can cause fine disturbance of an electric field in a local area, and the fine disturbance is more easily detected in a high frequency band, so that phase angle fluctuation of the high frequency band is caused to be at a peak value. By accurately judging the frequency position of the peak value of the energy spectrum, different types of unfused defects existing in the melting interface can be accurately identified, and a powerful basis is provided for subsequent quality evaluation and repair measures.
In another preferred embodiment of the present invention, the distributed electrode group is arranged in the following manner:
In the axial direction of the electric melting sleeve, n groups of annular electrodes are reasonably arranged. Where n is a preset value determined according to various factors such as the length of the electric hot-melt sheath and the required detection accuracy, for example, the value of n is increased correspondingly for longer electric hot-melt sheaths to ensure that the entire axial range is adequately covered. Notably, there is axial overlap of the detection regions of adjacent ring electrodes. This axial overlap design is of great significance, and it avoids the occurrence of detection dead zones, enabling continuous and non-missing monitoring of the connection site in the axial direction. For example, if the detection area of one set of ring electrodes covers the axial length L, then the detection areas of adjacent ring electrodes overlap by a certain proportion (e.g., 30%), that is, the overlapping length is 0.3L, so that it is ensured that each position can be detected by at least two sets of ring electrodes over the entire axial length, and the reliability of detection is greatly improved.
Each group of ring electrodes comprises m layers of concentric ring electrodes with different radial directions, and the value of m is also a preset value determined according to detection requirements at different radial depths. Each layer of concentric ring electrode has a specific detection task, and from the inner wall to the outer wall of the electric melting sleeve, the concentric ring electrodes of different layers can respectively sense the electrical characteristic changes at different radial depth positions. In each layer of ring electrode, o electrode units are included, the number of o being a preset value determined according to the required detection resolution in the circumferential direction. The electrode units are uniformly distributed on the annular electrode in a circumferentially symmetrical manner, for example, if the circumference of one annular electrode is C, and o electrode units are uniformly distributed, the arc length between adjacent electrode units is C/o. This uniform distribution ensures the uniformity and comprehensiveness of the detection in the circumferential direction.
More critical is that each electrode unit is connected with a switching circuit. The switching circuit is just like an intelligent control hub, and can be used for carrying out diversified combination on different electrode units through flexible control functions. For example, at one moment, several adjacent electrode units in the same layer may be combined into one detection loop to detect the local electrical condition at the circumferential position, and at another moment, electrode units of different layers and at different circumferential positions may be combined to form one cross-layer and cross-circumference detection loop for analyzing the electrical relationship between different radial and circumferential positions. By means of the abundant and various combination modes, multiple groups of independent detection loops can be formed. The independent detection loops can detect the connection part of the electric melting sleeve from different angles and different dimensions, collect a large amount of electrical data, provide sufficient and comprehensive data support for subsequent defect judgment and analysis, and greatly improve the flexibility and accuracy of a monitoring system.
In a preferred case of this embodiment, locating the spatial distribution of the molten defects includes axial, radial and circumferential locating, the locating process being:
Axial positioning, namely, using the special design of an axial overlap detection region, developing deep analysis on impedance response gradient change of the region. The specific operation starts from a certain section of the melting interface, and the detection work is carefully carried out along the axial direction. During the detection process, the change condition of the impedance response gradient value is continuously monitored. The preset value mentioned here is a key reference value comprehensively determined through a large amount of experimental data and theoretical research on the connection of the polyurethane direct-buried insulating pipe electric melting sleeve. Once the impedance response gradient at a location is identified during the inspection as increasing beyond a preset value, the location is accurately marked as an axial defect onset. The inspection operation then continues to advance steadily in the axial direction until the impedance response gradient value decreases below the preset value at a location, which is then marked as an axial defect end point. In this way, the region between the axial defect start point and the axial defect end point is the location region of the defect in the axial direction. For example, if the preset value is set to X, when the impedance response gradient at a position is suddenly increased from a value smaller than X to x+Δx (Δx is an increment exceeding the preset value) during the axial detection, the position is the starting point, and when the impedance response gradient at a position is reduced from a value larger than X to X- Δx (Δx is a decrement lower than the preset value) during the subsequent detection, the position is the ending point, and the region between the two points is the axial defect positioning region.
Radial positioning, namely focusing the focus into the determined axial positioning area after axial positioning is completed. The region is distributed with concentric ring electrodes of different layers, and impedance response data of the concentric ring electrodes of different layers are collected. The sensitivity to defects varies due to the difference in distance between concentric ring electrodes at different radial positions and the molten layer. And calculating by using a special algorithm according to the impedance response difference of the concentric ring electrodes at different radial positions. For example, the concentric annular electrode layer where the defect is accurately calculated by comparing the characteristic of the impedance response curves of the electrodes of different layers, calculating the impedance difference ratio and the like. The radial range corresponding to the concentric ring electrode layer is the positioning range of the defect in the radial direction. For example, if three layers of concentric ring electrodes exist, the impedance responses of the electrodes are Z1, Z2 and Z3 respectively, and by analyzing the difference relationships between the electrodes, such as comparing the magnitudes of |z1-z2| and |z2-z3|, and combining the known distance relationships between the electrodes of different layers and the molten layer, the specific electrode layer where the defect is located can be determined, and thus the radial positioning range of the defect can be determined.
Circumferential positioning, namely after the axial positioning area and the radial positioning range are defined, collecting impedance response data generated for each detection loop in the range. The detection loops are formed by combining different electrode units, and the impedance response of the detection loops can reflect the characteristics of the molten layer in the circumferential direction. The impedance response difference of the detection loop is deeply analyzed, and the uniformity degree of the molten layer in the circumferential direction is calculated in a quantitative mode. The set ratio is also an important index determined through a large number of experiments and data analysis. If the impedance difference of any adjacent electrode unit exceeds a set proportion, for example, the set proportion is Y%, in the analysis process, when the proportion obtained by dividing the impedance difference of the adjacent electrode unit by the impedance value of one electrode unit is greater than Y%, the existence of the melting defect in the corresponding circumferential region can be judged. By the method, the positions of the defects can be accurately determined in the circumferential direction, and the omnibearing accurate positioning of the spatial distribution of the molten defects is realized.
In another preferred embodiment of the present invention, the method for constructing the preset melt interface uniformity model includes:
First, the related work was carried out under standard experimental conditions. The standard experimental conditions are carefully designed and strictly controlled, and all parameters including ambient temperature, humidity, pressure and the like are kept in a stable and repeatable state. Under such conditions, a fully sealed melt interface is monitored throughout and data acquired. In the whole electric melting sleeve heating process, different heating stages such as an initial heating stage, a rapid heating stage, a constant temperature melting stage and the like are covered, and the change condition of real part impedance along with time is carefully recorded at different temperatures. By long-time, multi-stage and multi-temperature point recording, a large amount of real part impedance-time data is collected, and then the data are collated and analyzed to draw a real part impedance attenuation curve. The curve intuitively reflects the change trend of the real part impedance with time under different heating conditions, and provides important basic data for subsequent model construction. Meanwhile, the fluctuation condition of the phase angle of the imaginary part under different frequencies is analyzed and extracted. By applying a professional signal processing algorithm and tool, the fluctuation characteristics of the imaginary phase angle under different frequencies are summarized and generalized to form an imaginary phase fluctuation template. And integrating relevant data such as a real part impedance attenuation curve, an imaginary part phase fluctuation template and the like to generate an impedance reference database. The database contains various electrical characteristic data under the condition of ideal uniform fusion interface, and provides rich and reliable reference basis for training and verification of subsequent models.
The fusion interface uniformity model mainly comprises two key parts, namely a relation model of a real part impedance gradient and a fusion layer thickness and an imaginary part phase fluctuation mode classification model.
And (3) for constructing a relation model of the real part impedance gradient and the thickness of the molten layer, inputting real part impedance data in an impedance reference database into the convolutional neural network. The convolutional neural network is a powerful deep learning model and has excellent feature extraction and learning capabilities. By letting the convolutional neural network learn the real part impedance data, it can automatically identify the variation characteristics of the real part impedance at different positions and under different conditions. For example, the law of change in real impedance may vary in different heating phases, different temperature environments, different material properties, etc. The convolutional neural network can capture the fine change characteristics through the study and analysis of a large amount of data, and establishes a nonlinear mapping relation between a real part impedance gradient and the thickness of a molten layer. The nonlinear mapping relation considers the influence of various complex factors, and can more accurately describe the internal relation between the real part impedance gradient and the thickness of the molten layer, so that a relation model of the real part impedance gradient and the thickness of the molten layer is obtained.
And (3) for constructing the imaginary part phase fluctuation mode classification model, inputting imaginary part phase fluctuation template data in the impedance reference database into a support vector machine algorithm. The template data contains imaginary phase fluctuation modes corresponding to different defect types, such as macroscopic cracks, microscopic bubbles, impurities and the like, which can cause the imaginary phase angle to present different fluctuation characteristics. The support vector machine algorithm is an effective classification algorithm that performs classification training on the template data. In the training process, the support vector machine algorithm analyzes the imaginary part phase fluctuation characteristics corresponding to different defect types and finds out the difference and rule between the imaginary part phase fluctuation characteristics. And then storing the imaginary part phase fluctuation characteristics corresponding to the different defect types to generate a plurality of phase fingerprint identification libraries. The phase fingerprint identification libraries are just like a 'defect feature dictionary', and possible defect types can be rapidly and accurately judged according to the actually monitored imaginary phase fluctuation conditions, so that an imaginary phase fluctuation mode classification model is obtained.
And finally, inputting real-time monitoring data into the trained fusion interface uniformity model. The model analyzes and evaluates real-time data based on knowledge learned and trained previously. For real impedance data, a melt quality score is output that intuitively reflects the quality of the current melt interface in terms of real impedance. For the imaginary phase data, a defect confidence parameter is output that indicates how well the current imaginary phase fluctuation matches the known defect type, thereby helping to determine if a defect exists and how likely it is.
In another preferred embodiment of the present invention, further comprising:
On the basis of the accurate axial positioning, radial positioning and circumferential positioning of the defects, the important parameter of heating time is fully considered. By collecting position data of the defects in the axial direction, the radial direction and the circumferential direction at different heating moments and applying an advanced three-dimensional modeling algorithm and a data analysis technology, a defect three-dimensional evolution model is built.
The model has a powerful function and can dynamically present the increase rate of the defect volume along with the heating time. For example, in the initial stage of heating, by measuring and calculating the dimensional change of the defect in three dimensions at different time points, the volume calculation formula is utilized to obtain the increase value of the defect volume at the stage, and the increase rate of the volume with time is further calculated. As the heating progresses, the data are continuously updated, thereby obtaining a complete defect volume growth rate change curve with heating time.
Meanwhile, the model can accurately depict the change track of the defect shape position. During the heating process of the electric melting sleeve, the shape of the defect may be gradually changed from an initial irregular state, for example, a tiny crack may be extended and spread over time, and bubbles may be fused or deformed. The model displays the change condition of the defect shape in all directions and the position moving track thereof in space in a three-dimensional visual mode through continuous tracking and analysis of axial, radial and circumferential positioning data.
The foregoing describes one embodiment of the present invention in detail, but the description is only a preferred embodiment of the present invention and should not be construed as limiting the scope of the invention. All equivalent changes and modifications within the scope of the present invention are intended to be covered by the present invention.
Claims (9)
1. The method for monitoring the connection of the electric melting sleeve of the polyurethane direct-buried heat preservation pipe is characterized by comprising the following steps of:
embedding distributed electrode groups in annular contact surfaces at two sides of the electric melting sleeve, wherein the distributed electrode groups and a conductive enhancement structure in the polyurethane heat insulation layer form an electric coupling network;
in the process of electrifying and heating the electric melting sleeve, a dynamically modulated broadband alternating current signal is applied to the electrode group, and the frequency range of the broadband alternating current signal covers the dielectric relaxation frequency band of the melting interface;
Collecting voltage response signals of each electrode pair in the distributed electrode group in real time, and calculating complex impedance spectrums of the electric melting sleeve based on the voltage response signals, wherein the complex impedance spectrums comprise real-part impedance components and imaginary-part impedance components;
analyzing nonlinear attenuation characteristics of the real part impedance component, and generating a fusion defect early warning signal if the nonlinear attenuation characteristics do not accord with an expected rule;
The dielectric abnormal characteristics of the microstructure of the melting interface are extracted by analyzing the fluctuation rule of the phase angle of the imaginary impedance component along with the frequency change, the dielectric abnormal characteristics are matched with a preset melting interface uniformity model, and if the matching result exceeds a preset tolerance range, a melting defect early warning signal is generated;
the spatial distribution of the fusion defect is localized based on the impedance response of the distributed electrode set.
2. The method for monitoring the connection of the electric melting sleeve of the polyurethane direct-buried insulating pipe according to claim 1, wherein the electric conduction reinforcing structure is a wire mesh or a carbon fiber array embedded in the polyurethane insulating layer, the wire mesh or the carbon fiber array is uniformly distributed along the circumferential direction of the polyurethane insulating layer, and the wire mesh or the carbon fiber array is electrically connected with the annular electrode mounting surface of the distributed electrode group in the full circumferential direction through welding or conductive adhesive.
3. The method for monitoring the connection of the electric melting sleeve of the polyurethane direct-buried insulating pipe according to claim 1, wherein the dynamic modulation mode of the broadband alternating current signal comprises the following steps:
marking the time interval of the electrifying and heating of the electric melting sleeve as [ t1, t2], wherein the broadband alternating current signal comprises a low-frequency-band continuous sweep frequency signal and a high-frequency-band pulse modulation signal;
When the frequency range is in the time interval of [ t1, t0], t0 is a preset value, a low-frequency-band continuous sweep frequency signal is applied, and the frequency range of the low frequency band corresponds to the response frequency band of the overall conductivity of the polyurethane material in a molten state;
When the frequency range is in the time interval (t 0, t 2), a high-frequency-band pulse modulation signal is superimposed on the basis of a low-frequency-band continuous sweep frequency signal, wherein the frequency range of the high frequency band corresponds to a local dielectric relaxation frequency band caused by microscopic defects of a melting interface, and the microscopic defects comprise bubbles or impurities;
In the electric heating sleeve electrifying and heating process, impedance response data of the electrode group are collected in real time, the interval size of frequency change in the low-frequency-band continuous sweep frequency signal and the ratio of pulse duration to period in the high-frequency-band pulse modulation signal are adjusted according to the impedance response data, and the broadband alternating current signal is adaptively matched with the melting process of the polyurethane material.
4. The method for monitoring the connection of the electric melting sleeve of the polyurethane direct-buried insulating pipe according to claim 1, wherein the calculation of the complex impedance spectrum specifically comprises the following steps:
Synchronous detection processing is carried out on the voltage response signal, a part which is in the same frequency and phase as the excitation signal in the voltage response signal is separated and marked as a real part voltage component, and a part which is in quadrature with the excitation signal in phase is separated and marked as an imaginary part voltage component;
Calculating the real part impedance through the real part voltage component, obtaining the change rate of the real part impedance in a radial space, constructing a dynamic distribution model of the thickness of the molten layer, calculating the imaginary part impedance based on the imaginary part voltage component, representing the value of the imaginary part impedance in a cloud picture form by taking the spatial position as a coordinate, generating a dielectric characteristic distribution cloud picture, and obtaining the local extreme point of the imaginary part impedance in the cloud picture.
5. The method for monitoring the connection of the electric melting sleeve of the polyurethane direct-buried insulating pipe according to claim 4, wherein the process for extracting the dielectric anomaly characteristic of the microstructure of the melting interface comprises the following steps:
Performing multi-scale time-frequency analysis on the imaginary impedance component, decomposing the signal of the imaginary impedance component into different frequency components, acquiring fluctuation changes of the different frequency components at different time points, and extracting non-stationary fluctuation components of the phase angle at a specific frequency band;
constructing an energy spectrum according to the extracted non-stationary fluctuation component of the phase angle, wherein the energy spectrum is used for representing energy distribution of phase angle fluctuation under different frequencies, and calculating an integral value of the energy spectrum in a preset defect characteristic frequency band, wherein the integral value represents phase angle fluctuation energy of all frequencies in the frequency band;
the frequency position of a peak value in the energy spectrum is obtained, when a low-frequency energy peak appears in the energy spectrum, the unfused defect is a macroscopic crack defect, and when a high-frequency energy peak appears in the energy spectrum, the unfused defect is a microscopic bubble/impurity defect.
6. The method for monitoring the connection of the electric melting sleeve of the polyurethane direct-buried insulating pipe according to claim 1, wherein the distributed electrode group is arranged in the following manner:
In the axial direction of the electric melting sleeve, n groups of annular electrodes are arranged, the detection areas of the adjacent annular electrodes are axially overlapped, each group of annular electrodes comprises m layers of concentric annular electrodes with different radial directions, each layer of annular electrodes comprises o electrode units, the electrode units are distributed on the annular electrodes in a circumferentially symmetrical mode, n, m and o are preset values, each electrode unit is connected with a switching circuit, and different electrode units are combined in different ways through the control of the switching circuits to form a plurality of groups of independent detection loops.
7. The method for monitoring the connection of the electric melting sleeve of the polyurethane direct-buried insulating pipe according to claim 6, wherein the spatial distribution of the positioning melting defects comprises axial positioning, radial positioning and circumferential positioning, and the positioning process is as follows:
Acquiring impedance response gradient change of an axial overlap detection area, starting axial detection from one end of a melting interface, marking the position as an axial defect starting point when the impedance response gradient at any position is identified to be increased beyond a preset value, continuing to identify along the axial direction until the impedance response gradient at any position is lower than the preset value, marking the position as an axial defect ending point, and obtaining an area between the defect starting point and the defect ending point as an axial positioning area of the defect;
Acquiring impedance responses of concentric ring electrodes of different layers in the axial positioning area, and calculating concentric ring electrode layers where the defects are located according to impedance response differences of the concentric ring electrodes of different radial positions, namely, the radial positioning range of the defects;
and obtaining impedance response generated by each detection loop in the radial positioning range of the axial positioning area, calculating the uniformity degree of the molten layer in the circumferential direction by analyzing impedance response differences of the detection loops, and judging that the corresponding circumferential area has the molten defect if the impedance difference of any adjacent electrode units exceeds a set proportion.
8. The method for monitoring the connection of the electric melting sleeve of the polyurethane direct-buried insulating pipe according to claim 1, wherein the method for constructing the preset melting interface uniformity model comprises the following steps:
Monitoring and data acquisition are carried out on a completely sealed melting interface under standard experimental conditions, and the change condition of real part impedance along with time is recorded under different heating stages and different temperatures to form a real part impedance attenuation curve;
the melting interface uniformity model comprises a relation model of a real part impedance gradient and a melting layer thickness and an imaginary part phase fluctuation mode classification model;
Inputting real part impedance data in an impedance reference database into a convolutional neural network, learning the change characteristics of the real part impedance under different positions and different conditions, establishing a nonlinear mapping relation between the real part impedance gradient and the thickness of a molten layer, and obtaining a relation model of the real part impedance gradient and the thickness of the molten layer;
Inputting imaginary part phase fluctuation template data in an impedance reference database into a support vector machine algorithm, wherein the template data comprises imaginary part phase fluctuation modes corresponding to different defect types, the support vector machine algorithm carries out classification training on the template data, stores imaginary part phase fluctuation characteristics corresponding to different defect types, generates a plurality of phase fingerprint identification libraries, and obtains an imaginary part phase fluctuation mode classification model;
Inputting the real-time monitoring data into a trained fusion interface uniformity model, and outputting a real-part impedance data fusion quality score and defect confidence coefficient parameters of the imaginary part phase data.
9. The method for monitoring the connection of the electric melting sleeve of the polyurethane direct-buried insulating pipe of claim 7, further comprising:
Based on the axial positioning, radial positioning, circumferential positioning and heating time parameters, a defect three-dimensional evolution model is established, and the defect three-dimensional evolution model comprises the growth rate of the defect volume along with the heating time and the change track of the shape position.
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