Insulation state detection method, system, equipment and medium

Abstract

The invention provides an insulation state detection method, system, equipment and medium, and relates to the field of electronic device detection.The method comprises the steps that a discharge signal of a power module is obtained, high-pass filtering and wavelet noise reduction are conducted on the discharge signal, and a discharge pulse is obtained; recording the morphology change of the bubbles at the three bonding points of the substrate, the electrode and the silica gel of the power module; analyzing the discharge pulse based on a phase resolution partial discharge map to obtain partial discharge parameter changes, and classifying the partial discharge parameter changes to obtain insulation defect types; and performing evaluation according to the morphology change of the bubbles and the insulation defect type to obtain an insulation degradation state. On the basis of collaborative analysis of bubble evolution and discharge characteristics, the insulation state of the high-voltage power module is monitored, in-situ observation of bubble evolution of a glue-solid interface is realized, discharge signal characteristics are extracted, and a mapping relation of bubble form-discharge mode-signal parameters is established.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of electronic device detection, in particular to a method, system, device and medium for insulating state detection. BACKGROUND

[0002] With the development of power electronic devices towards high frequency and high power density, power modules such as Insulated Gate Bipolar Transistor (IGBT) are prone to local electric field distortion due to dielectric constant mismatch and geometric discontinuity under high-frequency square wave voltage, especially at the Triple Junction (TJ) of the substrate-electrode-silicone gel, the electric field strength can be several times the average field strength, resulting in frequent Interfacial Partial Discharge (IPD), which seriously threatens the insulation performance and service life of the power module.

[0003] In the prior art, although attention has been paid to the electric field distribution and discharge phenomenon at the triple junction, in actual working conditions, the power module is faced with high-frequency square wave voltage, and the existing research results based on power frequency or low-frequency voltage are obviously inconsistent with the actual high-frequency square wave working condition, which cannot provide effective guidance for actual operation; and there is a close coupling relationship between the generation, evolution and discharge behavior of bubbles, and the in-situ observation and system analysis of the dynamic coupling process lack the matching of the coupling relationship between the partial discharge signal and the bubble shape, it is difficult to accurately capture the partial discharge signal to infer the shape and dynamic change of the bubble, and it is difficult to realize accurate detection and evaluation of the insulation state. SUMMARY

[0004] The present application provides a method, system, device and medium for insulating state detection, which can monitor the interface discharge and bubble evolution process in real time and evaluate the insulation state accordingly.

[0005] To achieve the above-mentioned purpose, the technical solutions adopted by the present application are as follows: Obtain the discharge signal of the power module, high-pass filter and wavelet denoise the discharge signal to obtain the discharge pulse; Record the morphology change of the bubble at the Triple Junction of the substrate-electrode-silicone gel of the power module; Analyze the discharge pulse based on phase-resolved partial discharge pattern to obtain the change of partial discharge parameters, classify the change of partial discharge parameters to obtain the insulation defect type; According to the morphology change of the bubble and the insulation defect type, the insulation deterioration state is obtained.

[0006] In some embodiments, the step of obtaining the discharge signal of the power module, high-pass filtering the discharge signal and wavelet denoising to obtain the discharge pulse includes: The discharge signal generated by the insulating medium of the power module under the action of the electric field is collected by a high-frequency sensor; The low-frequency noise is filtered out by a 400MHz high-pass filter, the signal is multi-scale decomposed by wavelet transform, and the high-frequency noise coefficient is removed to obtain the discharge pulse; The discharge pulse is reconstructed to obtain the waveform of the discharge pulse.

[0007] In some embodiments, The step of recording the morphology change of the bubble at the substrate-electrode-silicon gel three junction point of the power module includes: Based on the shape of the bubble at the substrate-electrode-silicon gel three junction point of the power module at the moment of bubble generation, the three-dimensional profile of the bubble is obtained to obtain the initial morphology data of the bubble; The change of the bubble under the action of the electric field is continuously collected to obtain time sequence morphology parameters and corresponding images, and the evolution data set of the morphology change of the bubble is fused.

[0008] In some embodiments, the step of analyzing the discharge pulse based on the phase-resolved partial discharge pattern to obtain the partial discharge parameter change includes: The discharge pulse is phase-labeled, and the discharge pulse in each phase window of the label is counted to calculate the period, average discharge amplitude, and maximum discharge amplitude of each phase window; A two-dimensional PRPD pattern is drawn with phase as the horizontal axis and discharge amplitude as the vertical axis; Based on the two-dimensional PRPD pattern, feature parameters are extracted to obtain the partial discharge parameter change, wherein the partial discharge parameter change includes the evolution of the discharge phase, amplitude, and frequency over time.

[0009] In some embodiments, the step of classifying the partial discharge parameter change to obtain the insulation defect type includes: A feature vector set is constructed for each insulation defect type; The partial discharge parameter change is classified, the similarity of the partial discharge parameter change and the feature vector set is calculated, and the insulation defect type corresponding to the feature vector with a similarity exceeding a threshold is obtained.

[0010] In some embodiments, the step of evaluating the insulation deterioration state according to the morphology change of the bubble and the insulation defect type includes: A mapping relationship between defects and bubbles is established, and a correlation degree is calculated to obtain the correlation between defects and bubbles; constructing an insulation deterioration state index based on the defect-bubble correlation, wherein the insulation deterioration state index comprises an insulation residual life; evaluating the bubble morphology change and the insulation defect type according to the insulation deterioration state index to obtain an insulation deterioration state.

[0011] In some embodiments, the bubble morphology change comprises an initial no-bubble stage, a solitary micro-bubble appearance stage, a bubble ellipse expansion stage, and a bubble through-breakdown stage.

[0012] The present application provides a system for insulation state detection, comprising: an acquisition unit configured to acquire a discharge signal of a power module, perform high-pass filtering and wavelet denoising on the discharge signal, and obtain a discharge pulse; a bubble unit configured to record a bubble morphology change at a substrate-electrode-silicone gel three-joint point of the power module; an analysis unit configured to analyze the discharge pulse based on a phase-resolved partial discharge pattern, obtain a partial discharge parameter change, classify the partial discharge parameter change, and obtain an insulation defect type; an evaluation unit configured to evaluate according to the bubble morphology change and the insulation defect type to obtain an insulation deterioration state.

[0013] The present application provides a computer device, comprising: at least one processor; and a memory storing a computer program capable of running on the processor, wherein the processor executes the program to perform the steps of the method for insulation state detection.

[0014] The present application provides a computer readable storage medium storing a computer program, wherein the computer program is executed by a processor to perform the steps of the method for insulation state detection.

[0015] Compared with the prior art, the present application has the following beneficial effects: The present application provides a method, system, device and medium for insulation state detection, comprising: acquiring a discharge signal of a power module, performing high-pass filtering and wavelet denoising on the discharge signal, and obtaining a discharge pulse; recording a bubble morphology change at a substrate-electrode-silicone gel three-joint point of the power module; analyzing the discharge pulse based on a phase-resolved partial discharge pattern to obtain a partial discharge parameter change, classifying the partial discharge parameter change to obtain an insulation defect type; and evaluating according to the bubble morphology change and the insulation defect type to obtain an insulation deterioration state.

[0016] The application is based on bubble evolution and discharge characteristic collaborative analysis, monitors the insulation state of a high-voltage power module, realizes in-situ observation of bubble evolution of a glue-solid interface, extracts a discharge signal characteristic, and establishes a mapping relationship of bubble morphology-discharge mode-signal parameter. The application realizes effective extraction of a weak discharge signal in a strong electromagnetic interference environment, clearly defines the four-stage corresponding relationship of interface discharge and bubble evolution, provides a visual basis for insulation state evaluation, provides theoretical support for life prediction and structure optimization of the power module, and provides guidance for manufacturing process, material selection and reliability design of the power module. BRIEF DESCRIPTION OF DRAWINGS

[0017] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or the prior art description. Obviously, the drawings in the following description only constitute some embodiments of the present application, and for those skilled in the art, other embodiments can be obtained without creative labor on the basis of these drawings.

[0018] Figure 1 A flow chart of a method for detecting an insulation state is provided for the present application.

[0019] Figure 2 A system module diagram of a system for detecting an insulation state is provided for the present application.

[0020] Figure 3 A structural schematic diagram of an embodiment of a computer device is provided for the present application.

[0021] Figure 4 A structural schematic diagram of an embodiment of a computer readable storage medium is provided for the present application.

[0022] Figure 5 A packaging insulation interface discharge test platform architecture diagram of a system for detecting an insulation state is provided for the present application.

[0023] Figure 6 A glue-solid interface discharge signal comparison diagram before and after noise reduction of an embodiment of a method for detecting an insulation state is provided for the present application.

[0024] Figure 7 An initial no-bubble stage diagram of an embodiment of a method for detecting an insulation state is provided for the present application.

[0025] Figure 8 An isolated micro-bubble appearance stage diagram of an embodiment of a method for detecting an insulation state is provided for the present application.

[0026] Figure 9 A bubble ellipse expansion stage diagram of an embodiment of a method for detecting an insulation state is provided for the present application.

[0027] Figure 10 Figure 1 is a bubble throughout breakdown stage diagram of an embodiment of the insulation state detection method provided by the present application.

[0028] Figure 11 Figure 2 is a PRPD spectrum of interface discharge at different stages of an embodiment of the insulation state detection method provided by the present application Figure 1 .

[0029] Figure 12 Figure 3 is a PRPD spectrum of interface discharge at different stages of an embodiment of the insulation state detection method provided by the present application Figure 2 .

[0030] Figure 13 Figure 4 is a PRPD spectrum of interface discharge at different stages of an embodiment of the insulation state detection method provided by the present application Figure 3 .

[0031] Figure 14 Figure 5 is a PRPD spectrum of interface discharge at different stages of an embodiment of the insulation state detection method provided by the present application Figure 4 .

[0032] Figure 15 Figure 6 is a statistical diagram of total discharge amplitude and discharge times changing with time of an embodiment of the insulation state detection method provided by the present application.

[0033] Figure 16 Figure 7 is a statistical diagram of maximum discharge amplitude and average amplitude changing with time of an embodiment of the insulation state detection method provided by the present application. DETAILED DESCRIPTION

[0034] The present application will be further described below in conjunction with the accompanying drawings. The following examples are only used to more clearly illustrate the technical solutions of the present application, and cannot be used to limit the protection scope of the present application. It should be noted that the following detailed description is exemplary, and is intended to provide further description of the present application.

[0035] It should be noted that all the expressions of first and second in the embodiments of the present application are used to distinguish two same name non-identical entities or non-identical parameters, and the first and second are only for the convenience of description, and should not be understood as a limitation of the embodiments of the present application. The subsequent embodiments will not be described one by one.

[0036] The present application provides a kind of insulation state detection method, please refer to Figure 1 , comprising: To achieve the above object, the technical scheme adopted by the present application is as follows: S1, obtain the discharge signal of power module, carry out high-pass filtering to the discharge signal and wavelet denoising, and obtain discharge pulse; S2, record the morphology change of the bubble at the substrate-electrode-silicone gel three junction point of the power module; S3, analyze the discharge pulse based on the phase resolved partial discharge pattern, obtain the partial discharge parameter change, classify the partial discharge parameter change, and obtain the insulation defect type; S4, evaluate according to the morphology change of the bubble and the insulation defect type, and obtain the insulation deterioration state.

[0037] The application combines the actual operation process as follows: Step 1: build a test platform: including a high-frequency square wave power supply, a discharge model of a power module structure, an ultra high frequency (UHF) sensor, a high-pass filter, an electron microscope and a signal processing unit; Step 2: signal acquisition and processing: the UHF sensor is used to collect the discharge signal, after 400MHz high-pass filtering, the wavelet denoising is used to extract the discharge pulse; Step 3: in-situ observation of bubble evolution: the morphology change of the bubble at the three junction points is recorded in real time by the electron microscope, which is divided into four stages: initial no bubble, isolated bubble, elliptical expansion and through breakdown; Step 4: discharge feature extraction: based on the phase resolved partial discharge (PRPD) pattern, the evolution of the discharge phase, amplitude and frequency with time is analyzed; Step 5: insulation state evaluation: according to the discharge frequency, amplitude growth trend and bubble morphology change, the insulation deterioration state evaluation stage.

[0038] First, the discharge signal of the power module is obtained, then the low-frequency interference is removed by high-pass filtering, and then the wavelet denoising is used to further eliminate the noise influence, so as to obtain the pure discharge pulse. Avoid the interference of external interference signals on the subsequent analysis, ensure the accuracy and reliability of the analysis results based on the discharge pulse, and lay a foundation for accurately judging the insulation deterioration state.

[0039] Based on the phase resolved partial discharge pattern, the characteristics of partial discharge at different phases can be clearly presented. Through the classification of the partial discharge parameter change, it can be accurately identified whether the insulation defect is internal air gap discharge or surface discharge.

[0040] The morphology change of the bubble and the insulation defect type are comprehensively considered for evaluation. The morphology change of the bubble can directly reflect the physical change of the internal insulation material, and the insulation defect type can reveal the nature of the insulation fault. Combined with the two, the one-sidedness of single factor evaluation is avoided, and the accuracy of the insulation deterioration state evaluation is greatly improved.

[0041] In some embodiments, referring to Figure 1 , the step of obtaining the discharge signal of the power module, high-pass filtering the discharge signal and wavelet denoising to obtain the discharge pulse includes: The discharge signal generated by the insulating medium of the power module under the action of the electric field is collected by a high-frequency sensor; The low-frequency noise is filtered out by a 400MHz high-pass filter, and the signal is decomposed by wavelet transform and the high-frequency noise coefficient is removed to obtain the discharge pulse; The discharge pulse is reconstructed to obtain the waveform of the discharge pulse.

[0042] The 400MHz high-pass filter is used to filter out low-frequency noise below 400MHz from the collected discharge signal, making the discharge signal purer.

[0043] Wavelet transform has the characteristic of multi-scale analysis, which can decompose signals of different scales. In the decomposition process, the high-frequency noise coefficient in the signal can be separated and removed. Unlike traditional fixed frequency filtering methods, wavelet denoising can adaptively process high-frequency noise according to the local characteristics of the signal, better preserving the details of the signal while removing noise, ensuring that key features such as the shape, amplitude, and duration of the discharge pulse are not destroyed, which is used for accurate analysis of the discharge process and identification of insulation fault types.

[0044] The reconstructed waveform can accurately reflect the discharge of the insulating medium under the action of the electric field.

[0045] In some embodiments, referring to Figure 1 , The step of recording the change in the morphology of the bubble at the substrate-electrode-silicone gel three junction of the power module includes: Based on the morphology of the bubble at the substrate-electrode-silicone gel three junction of the power module at the moment of bubble generation, the three-dimensional profile of the bubble is obtained to obtain the initial morphology data of the bubble; The change of the bubble under the action of the electric field is continuously collected to obtain time series of morphology parameters and corresponding images, and the evolution data set of the change in the morphology of the bubble is fused.

[0046] The initial state of the bubble contains key information at the time of generation, such as size, shape, position, etc. Different initial sizes of the bubble have different expansion speeds and rupture times under the action of the electric field.

[0047] The change of the bubble under the action of the electric field is continuously collected, and the morphology features of the bubble at each moment are recorded in detail to reflect the dynamic behavior of the bubble completely.

[0048] In some embodiments, referring to Figure 1, the step of analyzing the discharge pulse based on the phase-resolved partial discharge pattern to obtain the partial discharge parameter change comprises: phase labeling the discharge pulse, counting the discharge pulse in each labeled phase window, and calculating the period, average discharge amplitude, and maximum discharge amplitude of each phase window; a two-dimensional PRPD pattern is drawn with phase as the horizontal axis and discharge amplitude as the vertical axis; Based on the two-dimensional PRPD pattern, feature parameters are extracted to obtain the partial discharge parameter change, wherein the partial discharge parameter change includes the evolution of discharge phase, amplitude, and frequency over time.

[0049] The discharge pulse is phase labeled, and the discharge pulse in each phase window is counted to calculate the period, average discharge amplitude, and maximum discharge amplitude of each phase window. Different types of insulation defects produce partial discharge with specific distribution patterns in phase. Internal air gap discharge is concentrated in a specific phase range of the voltage rising edge and falling edge, while the phase distribution of surface discharge is relatively wide.

[0050] The calculation of average discharge amplitude and maximum discharge amplitude can reflect the intensity and severity of the discharge. As the fault develops, the maximum discharge amplitude increases significantly, and through the PRPD pattern, the dynamic changes of the discharge amplitude can be observed comprehensively.

[0051] The PRPD pattern of internal air gap discharge usually presents a double-peak or multi-peak distribution, while the pattern of surface discharge may exhibit a single peak and a relatively wide phase distribution. By analyzing these feature parameters, the type of insulation fault can be accurately identified.

[0052] In some embodiments, referring to Figure 1 , the step of classifying the partial discharge parameter change to obtain the insulation defect type comprises: constructing a feature vector set for each type of insulation defect; Classifying the partial discharge parameter change, calculating the similarity of the partial discharge parameter change and the feature vector set, and obtaining the insulation defect type corresponding to the feature vector with a similarity exceeding a threshold.

[0053] Constructing a feature vector set for each type of insulation defect is an abstract and quantitative representation of the essential characteristics of insulation defects. By calculating the similarity of the partial discharge parameter change and the feature vector set, the matching insulation defect type can be more accurately found, avoiding classification errors caused by feature omission or inaccuracy, and greatly improving the accuracy of classification. The synergistic effect of multiple feature parameters is considered, which can more comprehensively evaluate the compatibility of the partial discharge parameter change and different insulation defect types. Even if a parameter is disturbed and abnormal, other parameters can still provide effective classification information, thereby reducing the risk of misjudgment and improving the reliability of the classification result.

[0054] In some embodiments, referring to Figure 1 , the step of evaluating the insulation deterioration state according to the morphology change of the bubble and the insulation defect type comprises: establishing a mapping relationship between the defect and the bubble and performing correlation degree calculation to obtain the correlation between the defect and the bubble; constructing an insulation deterioration state index based on the correlation between the defect and the bubble, wherein the insulation deterioration state index comprises an insulation remaining life; evaluating the morphology change of the bubble and the insulation defect type according to the insulation deterioration state index to obtain the insulation deterioration state.

[0055] The morphology change of the bubble can directly reflect the physical change inside or on the surface of the insulation material, and the insulation defect type clearly indicates the specific properties of the insulation failure. By establishing a mapping relationship between the two and performing correlation degree calculation, the insulation deterioration state can be comprehensively and comprehensively evaluated, avoiding the limitations of relying on a single factor for evaluation, and greatly improving the accuracy of the evaluation result.

[0056] Establishing a mapping relationship between the defect and the bubble and performing correlation degree calculation can accurately quantify the correlation between the morphology change of the bubble and the insulation defect type. Different types of insulation defects may cause different characteristic bubble morphology changes. According to the morphology change of the bubble, the type and severity of the insulation defect can be inferred. The insulation deterioration state index can dynamically reflect the deterioration process of the insulation material. As the insulation material ages and deteriorates, the morphology change of the bubble and the insulation defect type will continuously evolve, and the deterioration rate and remaining life of the insulation material can be understood in real time.

[0057] In some embodiments, referring to Figure 1 , the morphology change of the bubble comprises an initial no-bubble stage, an isolated micro-bubble appearance stage, a bubble ellipse expansion stage, and a bubble through breakdown stage.

[0058] These four stages clearly outline the whole process of the bubble from nothing to something, from small to large, and even to insulation breakdown. The initial no-bubble stage indicates that the insulation material is in a relatively good state, and there is no obvious physical change inside due to electric field, heat, etc. With the aggravation of insulation deterioration, it enters the isolated micro-bubble appearance stage, which marks the beginning of local physical or chemical changes inside the insulation material, such as material decomposition, gas precipitation, etc. The bubble ellipse expansion stage shows that the bubble is continuously growing and deforming under the action of electric field, pressure, etc., and the insulation deterioration is further developed. And the bubble through breakdown stage means that the insulation material has been unable to withstand voltage and has occurred breakdown failure, accurately grasping the different degrees and states of insulation deterioration.

[0059] The present application proposes a system for detecting the insulation state, referring toFigure 2 , comprising: An acquisition unit 100 configured to acquire a discharge signal of a power module, perform high-pass filtering and wavelet denoising on the discharge signal, and obtain a discharge pulse; A bubble unit 200 configured to record a topographic change of a bubble at a substrate-electrode-silicone gel three-joint point of the power module; An analysis unit 300 configured to analyze the discharge pulse based on a phase-resolved partial discharge pattern, obtain a partial discharge parameter change, and classify the partial discharge parameter change to obtain an insulation defect type; An evaluation unit 400 configured to evaluate according to the topographic change of the bubble and the insulation defect type to obtain an insulation deterioration state.

[0060] The system includes a high-frequency square wave power supply, a discharge model simulating a power module structure, an ultra-high frequency sensor, a high-pass filter, an electron microscope, and a signal processing unit. The high-pass filter is a 400MHz passive LC filter. The signal processing unit uses a wavelet denoising algorithm to process the discharge signal, and the sym8 wavelet basis function is preferred. The discharge characteristics include the phase distribution pattern in the PRPD pattern, the growth trend of the discharge frequency and amplitude, which are used for power module insulation state evaluation and life prediction.

[0061] In some embodiments, referring to Figures 5-16 , Figure 5 The figure shows a schematic diagram of a packaging insulation interface discharge test platform structure, including a high-frequency square wave power supply, a discharge model, a UHF sensor, a filter, an oscilloscope, and an electron microscope.

[0062] Figure 6 The figure is a comparison chart of the glue-solid interface discharge signal before and after denoising, showing good noise suppression effect and retaining the amplitude and phase information of the discharge pulse.

[0063] Figures 7-10 The figure is a microscopic image of the four stages of the bubble evolution process at the three-joint point, (a) initial stage without bubble; (b) isolated micro-bubble appearance stage; (c) bubble ellipse expansion stage; (d) bubble through breakdown stage, showing the whole process from perfect insulation to final breakdown.

[0064] Figures 11-14 The figure is the PRPD pattern of the interface discharge at different stages, showing the evolution process of the discharge phase from dispersion to concentration, and the shape from triangle to needle to multi-peak layered.

[0065] Figure 15 The figure is a statistical chart of the total amplitude of discharge and the number of discharges changing with time, reflecting the trend of discharge energy accumulation and frequency growth.

[0066] Figure 16 is a statistical chart of the maximum amplitude and the average amplitude of the discharge varying with time, showing the law that the discharge intensity increases with the insulation deterioration.

[0067] The detection method of the discharge at the adhesive interface of the high-voltage power module comprises the following steps: a) applying a high-frequency square wave voltage to the simulation sample; b) synchronously collecting the discharge signal and the bubble image; c) filtering and denoising the discharge signal; d) extracting the discharge amplitude, phase and frequency characteristics; e) dividing the insulation deterioration stages according to the bubble shape change.

[0068] Figure 5 As shown in the structural schematic diagram of the encapsulation insulation interface discharge test platform, the high-frequency square wave power supply HVP-22P(N) is used, the output is 0-22kV, the frequency is 0-100kHz, the rising / falling edge is adjustable, the discharge model is the direct bonded copper (DBC) structure, the copper electrode curvature radius is 0.38mm, the inter-electrode distance is 0.3mm, the UHF sensor has a bandwidth of 200MHz-2GHz, the filter is a 400MHz LC passive high-pass filter, and the oscilloscope and electron microscope are used.

[0069] In this embodiment, the parameters of the high-frequency square wave power supply are set as follows: Figure 5 As shown in the structural schematic diagram of the encapsulation insulation interface discharge test platform, the high-frequency square wave power supply HVP-22P(N) is used, the output is 0-22kV, the frequency is 0-100kHz, the rising / falling edge is adjustable, the discharge model is the direct bonded copper (DBC) structure, the copper electrode curvature radius is 0.38mm, the inter-electrode distance is 0.3mm, the UHF sensor has a bandwidth of 200MHz-2GHz, the filter is a 400MHz LC passive high-pass filter, and the oscilloscope and electron microscope are used.

[0070] In this embodiment, the TWUHF-G04 type ultra-high frequency sensor is used, and the effective measurement bandwidth is 200MHz-2GHz. The sensor axis is kept at a fixed distance of 5cm from the three junction points of the sample to optimize the signal receiving sensitivity.

[0071] In this embodiment, an LC passive high-pass filter with a cutoff frequency of 400MHz is connected in series between the sensor and the oscilloscope with a bandwidth ≥2GHz, so as to effectively suppress low-frequency interference. After the signal is filtered and wavelet denoised, the discharge characteristics are extracted.

[0072] In this embodiment, Figures 7-10are four-stage microscopic images of the bubble evolution process at the key three- junction point, using a 4K-resolution electron microscope with adjustable focal length, 20-200 times magnification continuously adjustable, and the lens pointing directly at the key three-junction point area of the sample. Through software control, strict synchronization with the discharge signal acquisition is realized, and the dynamic evolution process of the bubble is captured at a rate of 1-5 frames per second. All experiments are carried out in a constant temperature environment (25±1°C) to eliminate the influence of temperature fluctuations. According to the bubble morphology, the bubble is divided into four stages.

[0073] In this embodiment, the square wave power supply is started, the voltage is applied according to the above parameters, the UHF detection system and the electron microscope are started synchronously; the UHF signal is monitored in real time, and when the discharge initiation is detected, the voltage is stabilized at 6.5kV, and the continuous experiment is started. The system synchronously records three key data: ① the processed discharge pulse sequence (including amplitude, phase, time); ② the corresponding applied voltage waveform; ③ the high-definition image sequence of the three-junction point area triggered at a fixed time.

[0074] Figures 11-14 is the PRPD pattern drawn according to the interface discharge signal processed in step, which is divided into four stages, showing the process of discharge phase from dispersion to concentration, and morphology from triangle to needle to multi-peak stratification. Figure 6

[0075] The recorded discharge data is statistically analyzed, and the trend chart shown in Figure 15 , Figure 16 is drawn. The change of the total discharge amplitude and the number of discharges is analyzed. When the number of discharges per unit time appears accelerated growth, which is more than 50% than the previous stage, it indicates that the insulation enters the rapid deterioration period. Before the critical breakdown, the maximum discharge amplitude usually appears a significant jump, which increases by about 65% in this embodiment.

[0076] After the appearance of visible bubbles, the average discharge amplitude may decrease or slow down due to the explosive increase in the number of discharges, which marks the transition of the failure mode from material micro-damage to air gap ionization dominance. Combined with the change of bubble morphology from bubble nucleation to bubble directional expansion, accurate judgment of the insulation state from healthy to warning to critical can be realized.

[0077] Based on the same inventive concept, according to another aspect of the present application, as shown in Figure 3 , the embodiment of the present application also provides a computer device 30, which comprises a processor 310 and a memory 320, and the memory 320 stores a computer program 321 which can run on the processor, and the processor 310 executes the steps of the method as above when executing the program.

[0078] Based on the same inventive concept, according to another aspect of the present application, as shown in Figure 4 ​As shown, the embodiment of the present application further provides a computer readable storage medium 40, which stores a computer program 410 executed by a processor to perform the method as above.

[0079] The embodiment of the present application can also include a corresponding computer device. The computer device includes a memory, at least one processor, and a computer program stored on the memory and executable on the processor, and the processor executes the program to perform any of the above methods.

[0080] The memory is a non-volatile computer readable storage medium, which can be used to store non-volatile software programs, non-volatile computer executable programs and modules, such as program instructions / modules in the embodiments of the present application. The processor executes the non-volatile software programs, instructions and modules stored in the memory to perform various functional applications and data processing of the device, i.e. to implement the above method.

[0081] The memory can include a program storage area and a data storage area, wherein the program storage area can store an operating system and at least one application required by a function; the data storage area can store data created according to the use of the device, etc. In addition, the memory can include a high-speed random access memory, and can also include a non-volatile memory, such as at least one magnetic disk storage device, a flash memory device, or other non-volatile solid-state storage device. In the embodiments, the memory can optionally include a memory remotely arranged with respect to the processor, and these remote memories can be connected to the local module through a network. Examples of the above network include but are not limited to the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0082] Finally, it should be noted that those skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be completed by a computer program to instruct related hardware, and the program can be stored in a computer readable storage medium. When the program is executed, it can include the processes of the above-mentioned embodiments. The storage medium of the program can be a magnetic disk, an optical disk, a read-only memory (ROM) or a random access memory (RAM), etc. The above-mentioned embodiments of the computer program can achieve the same or similar effects as the corresponding any of the above-mentioned method embodiments.

[0083] Those of skill would further appreciate that the various illustrative logical blocks, modules, circuits, and algorithm steps described in connection with the disclosure herein can be implemented as electronic hardware, computer software, or combinations of both. To clearly illustrate this interchangeability of hardware and software, various illustrative components, blocks, modules, circuits, and steps have been described above generally in terms of their functionality. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the overall system. Skilled artisans can implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present embodiments.

[0084] The above are only exemplary embodiments of the present embodiments, but it should be noted that various changes and modifications can be made without departing from the scope of the present embodiments defined by the claims. The functions, steps and / or actions of the method claims described above need not be performed in any particular order. Unless explicitly stated, the ordinal use of terms such as first, second, etc. does not necessarily denote different or separate embodiments. Rather, such terms can be used interchangeably and / or syntactically acting on previously introduced-terminology to assist clarity in only certain non-limiting embodiments. Furthermore, although the elements of the present embodiments disclosed can be described or claimed in individual

[0085] It is to be understood that the singular forms "a," "an," and "the" include plural referents unless the context clearly dictates otherwise. It is to be further understood that the terms "comprising," "including," "having," and the like, when used in the present specification, specify the presence of stated features, integers, steps, operations, elements, or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, or groups thereof.

[0086] Those of ordinary skill in the art will appreciate that the above discussions related to various embodiments are merely illustrative and not intended to suggest restrictive embodiments of the present embodiments (including claims) which are limited in scope to the examples described. Embodiments of the present embodiments are also combinable with other embodiments or various features of the embodiments described above, and there are many other variations of the various aspects of the present embodiments as described above, which are not expressly mentioned or described herein. Accordingly, any and all modifications, variations or equivalent arrangements which do not depart from the spirit or scope of the present embodiments should be considered to be within the scope of the present embodiments.

Claims

1. A method of insulation condition detection, characterized by, The method comprises the following steps: acquiring a discharge signal of the power module, high-pass filtering and wavelet denoising the discharge signal to obtain a discharge pulse; recording the morphology change of the bubble at the substrate-electrode-silicone gel three junction point of the power module; analyzing the discharge pulse based on a phase-resolved partial discharge pattern to obtain a partial discharge parameter change, and classifying the partial discharge parameter change to obtain an insulation defect type; evaluating the bubble morphology change and the insulation defect type to obtain an insulation deterioration state.

2. The method of claim 1, wherein The step of acquiring the discharge signal of the power module, high-pass filtering and wavelet denoising the discharge signal to obtain the discharge pulse comprises: under the action of an electric field, the discharge signal generated by the insulating medium of the power module is collected by a high-frequency sensor to obtain the discharge signal; low-frequency noise is filtered out by a 400MHz high-pass filter, and a wavelet transform is used to perform multi-scale decomposition on the signal and remove high-frequency noise coefficients to obtain the discharge pulse; the discharge pulse is reconstructed to obtain the waveform of the discharge pulse.

3. The method of claim 1, wherein The step of recording the morphology change of the bubble at the substrate-electrode-silicone gel three junction point of the power module comprises: based on the shape of the bubble at the moment of bubble generation at the substrate-electrode-silicone gel three junction point of the power module, a three-dimensional profile of the bubble is acquired to obtain bubble initial morphology data; the change of the bubble under the action of an electric field is continuously collected to obtain time sequence morphology parameters and corresponding images, and evolution data sets of the bubble morphology change are fused.

4. The method of claim 2, wherein The step of analyzing the discharge pulse based on a phase-resolved partial discharge pattern to obtain a partial discharge parameter change comprises: phase labeling is performed on the discharge pulse, and the discharge pulse in each phase window of the labeled discharge pulse is counted to calculate the period, average discharge amplitude and maximum discharge amplitude of each phase window; a two-dimensional PRPD pattern is drawn with phase as the horizontal axis and discharge amplitude as the vertical axis; feature parameters are extracted based on the two-dimensional PRPD pattern to obtain the partial discharge parameter change, wherein the partial discharge parameter change includes the evolution of discharge phase, amplitude and frequency over time.

5. The method of claim 1, wherein The step of classifying the partial discharge parameter change to obtain an insulation defect type comprises: a feature vector set is constructed for each insulation defect type; the partial discharge parameter change is classified, the similarity of the partial discharge parameter change and the feature vector set is calculated, and the insulation defect type corresponding to the feature vector with a similarity exceeding a threshold is obtained.

6. The method of claim 1, wherein The step of evaluating the bubble morphology change and the insulation defect type to obtain an insulation deterioration state comprises: a mapping relationship between defects and bubbles is established, and correlation degree calculation is performed to obtain the correlation between defects and bubbles; an insulation deterioration state index is constructed based on the correlation between defects and bubbles, wherein the insulation deterioration state index includes an insulation remaining life; the bubble morphology change and the insulation defect type are evaluated based on the insulation deterioration state index to obtain the insulation deterioration state.

7. The insulation state detection method according to claim 1, wherein the bubble morphology change comprises an initial bubble-free stage, an isolated micro-bubble appearance stage, a bubble ellipse expansion stage and a bubble through breakdown stage.

8. A system for detecting an insulation condition, characterized by The method comprises the following steps: An acquisition unit configured to acquire a discharge signal of a power module, perform high-pass filtering and wavelet denoising on the discharge signal, and obtain a discharge pulse; A bubble unit configured to record a topographic change of a bubble at a substrate-electrode-silicone gel three-joint point of the power module; An analysis unit configured to analyze the discharge pulse based on a phase-resolved partial discharge pattern, obtain a partial discharge parameter change, classify the partial discharge parameter change, and obtain an insulation defect type; An evaluation unit configured to evaluate the topographic change of the bubble and the insulation defect type, and obtain an insulation deterioration state. 9.A computer device, comprising: at least one processor; and a memory storing a computer program capable of running on the processor, characterized in that the processor executes the program to perform the steps of the insulation state detection method according to any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, the computer program comprising instructions that, when executed by a computer, cause the computer to perform the method of any one of claims 1 to 9. The computer program is executed by the processor to perform the steps of the insulation state detection method according to any one of claims 1 to 7.

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