A method, system, device and medium for insulation condition detection

Abstract

This invention proposes a method, system, device, and medium for insulation condition detection, relating to the field of electronic device testing. The method includes: acquiring a discharge signal from a power module; performing high-pass filtering and wavelet noise reduction on the discharge signal to obtain a discharge pulse; recording the morphological changes of bubbles at the substrate-electrode-silica gel three-way junction of the power module; analyzing the discharge pulse based on a phase-resolved partial discharge spectrum to obtain changes in partial discharge parameters; classifying the changes in partial discharge parameters to obtain insulation defect types; and evaluating the insulation degradation state based on the morphological changes of the bubbles and the insulation defect types. This invention monitors the insulation state of high-voltage power modules based on the synergistic analysis of bubble evolution and discharge characteristics, achieving in-situ observation of bubble evolution at the gel-solid interface, extracting discharge signal features, and establishing a mapping relationship between bubble morphology, discharge mode, and signal parameters.

Description

Technical Field

[0001] This invention relates to the field of electronic device testing technology, and specifically to a method, system, device, and medium for insulation condition testing. Background Technology

[0002] As power electronic devices develop towards higher frequencies and higher power densities, power modules such as Insulated Gate Bipolar Transistors (IGBTs) are prone to local electric field distortion under high-frequency square wave voltages due to dielectric constant mismatch and geometric discontinuities. This is especially true at the triple junction (TJ) of the substrate-electrode-silicon gel, where the electric field strength can be several times that of the average field strength, leading to frequent interfacial partial discharge (IPD), which seriously threatens the insulation performance and lifespan of the power modules.

[0003] While existing technologies have focused on the electric field distribution and discharge phenomena at the three junction points, in actual operating conditions, power modules face high-frequency square wave voltages. Existing research results based on power frequency or low-frequency voltages are significantly inconsistent with actual high-frequency square wave operating conditions, failing to provide effective guidance for actual operation. Furthermore, there is a lack of understanding of the close coupling relationship between bubble generation, evolution, and discharge behavior. In-situ observation and system analysis of the dynamic coupling process lack matching of the coupling relationship between partial discharge signals and bubble morphology, making it difficult to infer the morphology and dynamic changes of bubbles by accurately capturing partial discharge signals, and thus hindering the accurate detection and assessment of insulation status. Summary of the Invention

[0004] This invention addresses the problems existing in the prior art by providing a method, system, device, and medium for insulation condition detection, which can monitor the interface discharge and bubble evolution process in real time and assess the insulation condition accordingly.

[0005] To achieve the above objectives, the technical solution adopted by the present invention is as follows:

[0006] The discharge signal of the power module is acquired, and the discharge signal is subjected to high-pass filtering and wavelet noise reduction to obtain the discharge pulse;

[0007] The morphological changes of bubbles were recorded at the three-way junction of the substrate, electrode, and silicon gel in the power module.

[0008] Based on phase-resolved partial discharge spectrum analysis of the discharge pulse, the changes in partial discharge parameters are obtained, and the changes in partial discharge parameters are classified to obtain the insulation defect type.

[0009] The insulation degradation state is obtained by evaluating the changes in the morphology of the bubbles and the types of insulation defects.

[0010] In some embodiments, the step of acquiring the discharge signal of the power module, performing high-pass filtering and wavelet noise reduction on the discharge signal to obtain a discharge pulse includes:

[0011] The discharge signal generated by the insulating medium of the power module under the action of an electric field is collected by a high-frequency sensor.

[0012] Low-frequency noise was filtered out by a 400MHz high-pass filter, and the signal was decomposed into multiple scales by wavelet transform and high-frequency noise coefficients were removed to obtain the discharge pulse.

[0013] The waveform of the discharge pulse is obtained by reconstructing the discharge pulse.

[0014] In some embodiments,

[0015] The step of recording the morphological changes of bubbles at the substrate-electrode-silicone gel three-way junction of the power module includes:

[0016] Based on the instantaneous morphology of the bubble at the three-way junction of the substrate-electrode-silicone gel in the power module, the three-dimensional contour of the bubble is obtained, and the initial morphology data of the bubble is obtained.

[0017] The changes of bubbles under the action of an electric field are continuously collected to obtain time series morphological parameters and corresponding images, which are then fused to obtain an evolutionary dataset of bubble morphological changes.

[0018] In some embodiments, the step of analyzing the discharge pulse based on a phase-resolved partial discharge spectrum to obtain changes in partial discharge parameters includes:

[0019] The discharge pulses are phase-marked, and the discharge pulses within each marked phase window are statistically analyzed to calculate the period, average discharge amplitude, and maximum discharge amplitude of each phase window.

[0020] A two-dimensional PRPD spectrum is plotted with phase as the horizontal axis and discharge amplitude as the vertical axis.

[0021] Feature parameters are extracted based on two-dimensional PRPD maps to obtain changes in partial discharge parameters, including the evolution of discharge phase, amplitude, and number of discharges over time.

[0022] In some embodiments, the step of classifying the changes in the partial discharge parameters to obtain the type of insulation defect includes:

[0023] Construct a set of feature vectors for each type of insulation defect;

[0024] The changes in partial discharge parameters are classified, and the similarity between the changes in partial discharge parameters and the feature vector set is calculated to obtain the insulation defect type corresponding to the feature vector with a similarity exceeding a threshold.

[0025] In some embodiments, the step of evaluating the insulation degradation state based on the morphological changes of the bubbles and the type of insulation defects includes:

[0026] Establish a mapping relationship between defects and bubbles, and calculate the correlation degree to obtain the correlation between defects and bubbles;

[0027] An insulation degradation status index is constructed based on the correlation between the defects and bubbles, wherein the insulation degradation status index includes the remaining insulation life.

[0028] The insulation degradation state is obtained by evaluating the morphological changes of the bubbles and the type of insulation defects based on the insulation degradation state index.

[0029] In some embodiments, the morphological changes of the bubble include an initial bubble-free stage, an isolated microbubble appearance stage, a bubble elliptical expansion stage, and a bubble penetration and breakdown stage.

[0030] This invention proposes a system for insulation condition detection, comprising:

[0031] The acquisition unit is configured to acquire the discharge signal of the power module, perform high-pass filtering and wavelet noise reduction on the discharge signal to obtain a discharge pulse;

[0032] A bubble unit is configured to record morphological changes of bubbles at the substrate-electrode-silicone gel junction of the power module.

[0033] The analysis unit is configured to analyze the discharge pulse based on a phase-resolved partial discharge spectrum, obtain changes in partial discharge parameters, classify the changes in partial discharge parameters, and obtain the type of insulation defect.

[0034] The evaluation unit is configured to evaluate the insulation degradation state based on the morphological changes of the bubbles and the type of insulation defects.

[0035] This invention proposes a computer device, comprising:

[0036] At least one processor; and a memory storing a computer program executable on the processor, wherein the processor, when executing the program, performs the steps of the method for detecting insulation status.

[0037] The present invention provides a computer-readable storage medium storing a computer program, which, when executed by a processor, performs the steps of the insulation state detection method.

[0038] Compared with the prior art, the present invention has the following beneficial effects:

[0039] This invention proposes a method, system, device, and medium for insulation condition detection. The method includes: acquiring a discharge signal from a power module; performing high-pass filtering and wavelet noise reduction on the discharge signal to obtain a discharge pulse; recording the morphological changes of bubbles at the substrate-electrode-silica gel three-way junction of the power module; analyzing the discharge pulse based on a phase-resolved partial discharge spectrum to obtain changes in partial discharge parameters; classifying the changes in partial discharge parameters to obtain insulation defect types; and evaluating the insulation degradation state based on the morphological changes of the bubbles and the insulation defect types.

[0040] This invention monitors the insulation status of high-voltage power modules based on the synergistic analysis of bubble evolution and discharge characteristics. It achieves in-situ observation of bubble evolution at the cement-solid interface, extracts discharge signal characteristics, and establishes a mapping relationship between bubble morphology, discharge mode, and signal parameters. This enables the effective extraction of weak discharge signals under strong electromagnetic interference environments; clarifies the four-stage correspondence between interface discharge and bubble evolution, providing a visual basis for insulation status assessment; provides theoretical support for power module lifetime prediction and structural optimization; and can provide guidance for power module manufacturing processes, material selection, and reliability design. Attached Figure Description

[0041] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other embodiments can be obtained based on these drawings without creative effort.

[0042] Figure 1 The present invention provides a flowchart of an insulation condition detection method.

[0043] Figure 2 This invention provides a system module diagram for insulation condition detection.

[0044] Figure 3 A schematic diagram of the structure of an embodiment of the computer device provided by the present invention.

[0045] Figure 4 This is a schematic diagram of an embodiment of the computer-readable storage medium provided by the present invention.

[0046] Figure 5 This invention provides an architecture diagram of a packaged insulation interface discharge test platform for an insulation state detection system.

[0047] Figure 6 A comparison of the discharge signals at the glue-solid interface before and after noise reduction in an embodiment of the insulation state detection method provided by the present invention.

[0048] Figure 7 This is an initial bubble-free stage diagram of an embodiment of an insulation state detection method provided by the present invention.

[0049] Figure 8 An embodiment of an insulation condition detection method provided by the present invention is shown in the diagram of the stages of isolated microbubble appearance.

[0050] Figure 9 An embodiment of an insulation condition detection method provided by the present invention is shown in the bubble elliptical expansion stage diagram.

[0051] Figure 10 A diagram illustrating the bubble penetration and breakdown stage of an embodiment of an insulation condition detection method provided by the present invention.

[0052] Figure 11 An embodiment of the insulation condition detection method provided by the present invention: interfacial discharge PRPD patterns at different stages. Figure 1 .

[0053] Figure 12 An embodiment of the insulation condition detection method provided by the present invention: interfacial discharge PRPD patterns at different stages. Figure 2 .

[0054] Figure 13 An embodiment of the insulation condition detection method provided by the present invention: interfacial discharge PRPD patterns at different stages. Figure 3 .

[0055] Figure 14 An embodiment of the insulation condition detection method provided by the present invention: interfacial discharge PRPD patterns at different stages. Figure 4 .

[0056] Figure 15 This is a statistical graph showing the changes in total discharge amplitude and number of discharges over time in an embodiment of the insulation state detection method provided by the present invention.

[0057] Figure 16 This is a statistical graph showing the variation of the maximum and average discharge amplitudes over time in an embodiment of the insulation state detection method provided by the present invention. Detailed Implementation

[0058] The present invention will be further described below with reference to the accompanying drawings. The following embodiments are only used to more clearly illustrate the technical solutions of the present invention and should not be construed as limiting the scope of protection of the present invention. It should be noted that the following detailed descriptions are exemplary and intended to provide further explanation of this application.

[0059] It should be noted that all uses of "first" and "second" in the embodiments of the present invention are for the purpose of distinguishing two entities with the same name but different names or different parameters. It is clear that "first" and "second" are only for the convenience of description and should not be construed as limiting the embodiments of the present invention. Subsequent embodiments will not explain this in detail.

[0060] This invention proposes a method for insulation condition detection; please refer to [link / reference]. Figure 1 ,include:

[0061] To achieve the above objectives, the technical solution adopted by the present invention is as follows:

[0062] S1. Obtain the discharge signal of the power module, perform high-pass filtering and wavelet noise reduction on the discharge signal to obtain the discharge pulse;

[0063] S2. Record the morphological changes of bubbles at the three-way junction of the substrate, electrode, and silicon gel in the power module;

[0064] S3. Based on the phase-resolved partial discharge spectrum analysis, the discharge pulse is obtained to obtain the changes in partial discharge parameters. The changes in partial discharge parameters are classified to obtain the insulation defect type.

[0065] S4. Evaluate the insulation degradation state based on the morphological changes of the bubbles and the type of insulation defects.

[0066] The practical operation process of this invention is as follows:

[0067] Step 1: Set up the test platform: including a high-frequency square wave power supply, a discharge model of the power module structure, an ultra-high frequency (UHF) sensor, a high-pass filter, an electron microscope, and a signal processing unit;

[0068] Step 2: Signal Acquisition and Processing: The discharge signal is acquired using a UHF sensor, filtered by a 400MHz high-pass filter, and then extracted using wavelet noise reduction.

[0069] Step 3: In-situ observation of bubble evolution: The morphological changes of the bubble at the three junction points are recorded in real time using an electron microscope and divided into four stages: initial no bubble, isolated bubble, elliptical expansion, and through-breakdown.

[0070] Step 4: Discharge Feature Extraction: Analyze the evolution of discharge phase, amplitude, and number of discharges over time based on phase-resolved partial discharge (PRPD) maps.

[0071] Step 5: Insulation condition assessment: Based on the number of discharges, the trend of amplitude growth, and the changes in bubble morphology, the insulation deterioration condition is assessed.

[0072] First, the discharge signal from the power module is acquired. Then, a high-pass filter is used to remove low-frequency interference, followed by wavelet denoising to further eliminate noise effects, thus obtaining a pure discharge pulse. This avoids interference from external signals in subsequent analyses, ensuring the accuracy and reliability of the analysis results based on the discharge pulse, and laying the foundation for accurately determining the insulation degradation state.

[0073] Phase-resolved partial discharge (MRD) spectral analysis of discharge pulses can clearly reveal the characteristics of MDD at different phases. By classifying the changes in MDD parameters, different types of insulation defects can be accurately identified, such as internal air gap discharge or surface discharge.

[0074] The assessment comprehensively considers both the morphological changes of bubbles and the types of insulation defects. Changes in bubble morphology directly reflect the internal physical changes of the insulation material, while the types of insulation defects reveal the nature of the insulation fault. Combining these two aspects avoids the limitations of assessments based on a single factor and significantly improves the accuracy of insulation degradation status assessment.

[0075] In some embodiments, please refer to Figure 1 The steps of acquiring the discharge signal from the power module, performing high-pass filtering and wavelet noise reduction on the discharge signal to obtain the discharge pulse include:

[0076] The discharge signal generated by the insulating medium of the power module under the action of an electric field is collected by a high-frequency sensor.

[0077] Low-frequency noise was filtered out by a 400MHz high-pass filter, and the signal was decomposed into multiple scales by wavelet transform and high-frequency noise coefficients were removed to obtain the discharge pulse.

[0078] The waveform of the discharge pulse is obtained by reconstructing the discharge pulse.

[0079] A 400MHz high-pass filter is used to filter out low-frequency noise below 400MHz from the acquired discharge signal, making the discharge signal purer.

[0080] Wavelet transform possesses multi-scale analysis capabilities, enabling the decomposition of signals at different scales. During this decomposition, high-frequency noise figures can be separated and removed. Unlike traditional fixed-frequency filtering methods, wavelet denoising adaptively processes high-frequency noise based on the local characteristics of the signal. While removing noise, it better preserves the signal's detailed information, ensuring that key features such as the shape, amplitude, and duration of the discharge pulse are not compromised. This allows for accurate analysis of the discharge process and identification of insulation fault types.

[0081] The reconstructed waveform can accurately reflect the discharge situation generated by the insulating medium under the action of the electric field.

[0082] In some embodiments, please refer to Figure 1 ,

[0083] The step of recording the morphological changes of bubbles at the substrate-electrode-silicone gel three-way junction of the power module includes:

[0084] Based on the instantaneous morphology of the bubble at the three-way junction of the substrate-electrode-silicone gel in the power module, the three-dimensional contour of the bubble is obtained, and the initial morphology data of the bubble is obtained.

[0085] The changes of bubbles under the action of an electric field are continuously collected to obtain time series morphological parameters and corresponding images, which are then fused to obtain an evolutionary dataset of bubble morphological changes.

[0086] The initial state of a bubble contains key information about its formation, such as size, shape, and position. Bubbles of different initial sizes expand at different rates and burst at different times under the influence of an electric field.

[0087] The changes of bubbles under the action of an electric field are continuously collected, and the morphological characteristics of the bubbles at each moment are recorded in detail, so as to fully reflect the dynamic behavior of the bubbles.

[0088] In some embodiments, please refer to Figure 1 The step of analyzing the discharge pulse based on the phase-resolved partial discharge spectrum to obtain the changes in partial discharge parameters includes:

[0089] The discharge pulses are phase-marked, and the discharge pulses within each marked phase window are statistically analyzed to calculate the period, average discharge amplitude, and maximum discharge amplitude of each phase window.

[0090] A two-dimensional PRPD spectrum is plotted with phase as the horizontal axis and discharge amplitude as the vertical axis.

[0091] Feature parameters are extracted based on two-dimensional PRPD maps to obtain changes in partial discharge parameters, including the evolution of discharge phase, amplitude, and number of discharges over time.

[0092] The discharge pulses are phase-marked, and the discharge pulses within each phase window are counted. The period, average discharge amplitude, and maximum discharge amplitude of each phase window are calculated. Partial discharges caused by different types of insulation defects have specific phase distribution patterns. Internal air gap discharges are concentrated in a specific phase range between the voltage rising and falling edges, while the phase distribution of surface discharges is relatively broad.

[0093] The calculation of average and maximum discharge amplitudes can reflect the intensity and severity of the discharge. As the fault progresses, the maximum discharge amplitude increases significantly, and the dynamic changes in discharge amplitude can be comprehensively observed through PRPD plots.

[0094] The PRPD spectrum of internal air gap discharge typically exhibits a bimodal or multimodal distribution, while the spectrum of surface discharge may show a single peak with a broad phase distribution. By analyzing these characteristic parameters, the type of insulation fault can be accurately identified.

[0095] In some embodiments, please refer to Figure 1 The step of classifying the changes in the partial discharge parameters to obtain the type of insulation defect includes:

[0096] Construct a set of feature vectors for each type of insulation defect;

[0097] The changes in partial discharge parameters are classified, and the similarity between the changes in partial discharge parameters and the feature vector set is calculated to obtain the insulation defect type corresponding to the feature vector with a similarity exceeding a threshold.

[0098] Constructing a feature vector set for each type of insulation defect provides an abstract and quantitative representation of the essential characteristics of the insulation defect. By calculating the similarity between changes in partial discharge parameters and the feature vector set, the matching insulation defect type can be identified more accurately, avoiding classification errors caused by missing or inaccurate features and significantly improving classification accuracy. By comprehensively considering the synergistic effect of multiple feature parameters, the fit between changes in partial discharge parameters and different insulation defect types can be evaluated more comprehensively. Even if one parameter is disturbed and becomes abnormal, other parameters can still provide effective classification information, thereby reducing the risk of misjudgment and improving the reliability of the classification results.

[0099] In some embodiments, please refer to Figure 1 The step of evaluating the insulation degradation state based on the morphological changes of the bubbles and the type of insulation defects includes:

[0100] Establish a mapping relationship between defects and bubbles, and calculate the correlation degree to obtain the correlation between defects and bubbles;

[0101] An insulation degradation status index is constructed based on the correlation between the defects and bubbles, wherein the insulation degradation status index includes the remaining insulation life.

[0102] The insulation degradation state is obtained by evaluating the morphological changes of the bubbles and the type of insulation defects based on the insulation degradation state index.

[0103] Changes in bubble morphology can intuitively reflect physical changes inside or on the surface of insulating materials, while the type of insulation defect clarifies the specific nature of insulation faults. By establishing a mapping relationship between the two and calculating the correlation, the insulation degradation status can be comprehensively assessed, avoiding the limitations of relying on a single factor for assessment and greatly improving the accuracy of the assessment results.

[0104] Establishing a mapping relationship between defects and bubbles and calculating the correlation degree allows for precise quantification of the correlation between bubble morphology changes and insulation defect types. Different types of insulation defects may lead to different bubble morphology changes, and the type and severity of insulation defects can be inferred from these morphological changes. Insulation degradation status indicators can dynamically reflect the degradation process of insulation materials. As insulation materials age and deteriorate, the morphological changes of bubbles and the types of insulation defects continuously evolve, allowing for real-time monitoring of the degradation rate and remaining life of the insulation material.

[0105] In some embodiments, please refer to Figure 1 The morphological changes of the bubbles include an initial bubble-free stage, an isolated microbubble appearance stage, a bubble elliptical expansion stage, and a bubble penetration and breakdown stage.

[0106] These four stages clearly outline the entire process of bubbles forming, growing in size, and eventually leading to insulation breakdown. The initial bubble-free stage indicates that the insulating material is in a relatively good state, with no significant physical changes caused by factors such as electric fields and heat. As insulation deterioration intensifies, the stage of isolated microbubbles appears, marking the beginning of localized physical or chemical changes within the insulating material, such as material decomposition or gas evolution. The elliptical bubble expansion stage shows that the bubbles continue to grow and deform under the influence of electric fields and pressure, further developing insulation deterioration. The bubble penetration and breakdown stage signifies that the insulating material can no longer withstand the voltage, resulting in a breakdown fault. Accurately understanding the different degrees and states of insulation deterioration is crucial.

[0107] This invention proposes a system for insulation condition detection; please refer to [link / reference]. Figure 2 ,include:

[0108] The acquisition unit 100 is configured to acquire the discharge signal of the power module, perform high-pass filtering and wavelet noise reduction on the discharge signal to obtain the discharge pulse;

[0109] Bubble unit 200 is configured to record morphological changes of bubbles at the substrate-electrode-silicone gel junction of the power module;

[0110] Analysis unit 300 is configured to analyze the discharge pulse based on phase-resolved partial discharge spectrum, obtain changes in partial discharge parameters, classify the changes in partial discharge parameters, and obtain insulation defect types.

[0111] The evaluation unit 400 is configured to evaluate the insulation degradation state based on the morphological changes of the bubbles and the type of insulation defects.

[0112] The system includes a high-frequency square wave power supply, a discharge model simulating the 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 noise reduction algorithm to process the discharge signal, preferably employing the sym8 wavelet basis function. The discharge characteristics include the phase distribution pattern in the PRPD spectrum, and the increasing trends of the number of discharges and amplitude, which are used for power module insulation status assessment and lifetime prediction.

[0113] In some embodiments, please refer to Figures 5-16 , Figure 5 The diagram shows the structure of the packaged insulation interface discharge test platform, which includes a high-frequency square wave power supply, a discharge model, a UHF sensor, a filter, an oscilloscope, and an electron microscope.

[0114] Figure 6 The image shows a comparison of the discharge signals at the glue-solid interface before and after noise reduction, demonstrating a good noise suppression effect while preserving the amplitude and phase information of the discharge pulse.

[0115] Figure 7-10 These are microscopic images of the four stages of bubble evolution at the three junction points: (a) the initial bubble-free stage; (b) the stage of isolated microbubbles appearing; (c) the bubble elliptical expansion stage; and (d) the bubble penetration and breakdown stage, demonstrating the entire process from intact insulation to final breakdown.

[0116] Figure 11-14 These are PRPD maps of interface discharge at different stages, showing the evolution of discharge phase from dispersed to concentrated, and morphology from triangular to needle-like to multi-peak stratification.

[0117] Figure 15 It is a statistical graph showing the changes in total discharge amplitude and number of discharges over time, reflecting the trend of discharge energy accumulation and frequency increase.

[0118] Figure 16 It is a statistical graph showing the changes in the maximum and average discharge amplitude over time, demonstrating the pattern that the discharge intensity increases with insulation degradation.

[0119] The detection method for cement-bonded interface discharge in high-voltage power modules includes the following steps:

[0120] a) Apply a high-frequency square wave voltage to the simulated sample;

[0121] b) Synchronously acquire discharge signals and bubble images;

[0122] c) Filter and reduce noise in the discharge signal;

[0123] d) Extract discharge amplitude, phase, and frequency characteristics;

[0124] e) Divide the insulation degradation stages according to the changes in bubble morphology.

[0125] Figure 5 The diagram shows the structure of the packaged insulation interface discharge test platform, which includes a high-frequency square wave power supply: HVP-22P(N) type, output 0~22kV, frequency 0~100kHz, rise / fall time adjustable from 50~500ns; discharge model: simulated direct-bonded copper (DBC) ceramic substrate structure, copper electrode curvature radius 0.38mm, electrode spacing 0.3mm; UHF sensor: bandwidth 200MHz~2GHz; filter: 400MHz LC passive high-pass filter; oscilloscope and electron microscope.

[0126] In this embodiment, according to Figure 5 The diagram shows the structure of the packaged insulation interface discharge test platform. Wiring is performed, and the parameters of the high-frequency square wave power supply are set as follows: frequency 10kHz, pulse width 20μs, rise / fall edge 500ns; voltage is boosted to the discharge initiation voltage in 100V / s steps.

[0127] In this embodiment, a TWUHF-G04 ultra-high frequency sensor is used, with an effective measurement bandwidth of 200MHz to 2GHz. The sensor axis is kept at a fixed distance of 5cm from the three junctions of the sample to optimize signal reception sensitivity.

[0128] 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) to effectively suppress low-frequency interference. The discharge characteristics are extracted after the signal is filtered and subjected to wavelet noise reduction.

[0129] In this embodiment, Figures 7-10 These are microscopic images of the four stages of bubble evolution at the three-junction point, captured using a 4K resolution electron microscope with adjustable focal length and continuously adjustable magnification from 20x to 200x. The lens was directly aimed at the key three-junction point region of the sample. Software control ensured strict synchronization with the acquisition of discharge signals, capturing the dynamic evolution of the bubbles at a rate of 1-5 frames per second. All experiments were conducted under a constant temperature environment (25±1°C) to eliminate the influence of temperature fluctuations. Based on bubble morphology, the bubbles were divided into four stages.

[0130] In this embodiment, a square wave power supply is activated, and voltage is applied according to the above parameters. The UHF detection system and electron microscope are simultaneously turned on. The UHF signal is monitored in real time. Once the discharge initiation is detected, the voltage is stabilized at 6.5kV, and continuous experimentation begins. The system simultaneously records three key data streams: ① the processed discharge pulse sequence (including amplitude, phase, and time); ② the corresponding applied voltage waveform; and ③ a timed sequence of high-resolution images of the three junction area.

[0131] Figures 11-14 Is according to Figure 6 The PRPD spectrum of the interface discharge signal after the step processing is divided into 4 stages, showing the process of discharge phase from dispersed to concentrated, and morphology from triangular to needle-like to multi-peak layering.

[0132] Statistical analysis was performed on the recorded discharge data, and plotted as follows: Figure 15 , Figure 16 The trend graph shown illustrates the changes in the total discharge amplitude and the number of discharges. When the number of discharges per unit time accelerates, increasing by more than 50% compared to the previous stage, it indicates that the insulation is entering a period of rapid degradation. Before breakdown, the maximum discharge amplitude usually shows a significant jump, increasing by approximately 65% ​​in this example.

[0133] After the appearance of visible bubbles, the average discharge amplitude may decrease or its growth slows down due to a surge in the number of discharges, indicating a shift in failure mode from material micro-damage to air gap ionization dominance. By combining this with the transformation of bubble morphology from bubble nucleation to directional bubble expansion, precise assessment of the insulation state can be achieved, progressing from healthy to early warning and then to critical conditions.

[0134] Based on the same inventive concept, according to another aspect of the present invention, such as Figure 3 As shown, an embodiment of the present invention also provides a computer device 30, which includes a processor 310 and a memory 320. The memory 320 stores a computer program 321 that can be run on the processor. When the processor 310 executes the program, it performs the steps of the method described above.

[0135] Based on the same inventive concept, according to another aspect of the present invention, such as Figure 4 As shown, embodiments of the present invention also provide a computer-readable storage medium 40, which stores a computer program 410 that, when executed by a processor, performs the methods described above.

[0136] Embodiments of the present invention may also include a corresponding computer device. The computer device includes a memory, at least one processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes any of the methods described above when executing the program.

[0137] The memory, as a non-volatile computer-readable storage medium, 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 this application. The processor executes various functional applications and data processing of the device by running the non-volatile software programs, instructions, and modules stored in the memory, thereby implementing the above-described method.

[0138] The memory may include a program storage area and a data storage area. The program storage area may store the operating system and applications required for at least one function; the data storage area may store data created based on the use of the device. Furthermore, the memory may include high-speed random access memory and non-volatile memory, such as at least one disk storage device, flash memory device, or other non-volatile solid-state storage device. In embodiments, the memory may optionally include memory remotely located relative to the processor, which can be connected to the local module via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0139] Finally, it should be noted that those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, it can include the processes of the embodiments of the methods described above. The storage medium for the program can be a magnetic disk, optical disk, read-only memory (ROM), or random access memory (RAM), etc. The above computer program embodiments can achieve the same or similar effects as any of the corresponding foregoing method embodiments.

[0140] Those skilled in the art will also understand that the various exemplary logic blocks, modules, circuits, and algorithm steps described in conjunction with the disclosure herein can be implemented as electronic hardware, computer software, or a combination of both. To clearly illustrate this interchangeability between hardware and software, the functionality of various illustrative components, blocks, modules, circuits, and steps has been generally described. Whether this functionality is implemented as software or as hardware depends on the specific application and the design constraints imposed on the system as a whole. Those skilled in the art can implement the functionality in various ways for each specific application, but such implementation decisions should not be construed as departing from the scope of the embodiments disclosed herein.

[0141] The above are exemplary embodiments disclosed in this invention. However, it should be noted that various changes and modifications can be made without departing from the scope of the embodiments of this invention as defined by the claims. The functions, steps, and / or actions of the methods according to the disclosed embodiments described herein do not need to be performed in any particular order. The sequence numbers of the disclosed embodiments of this invention are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments. Furthermore, although the elements disclosed in the embodiments of this invention may be described or claimed individually, they may be understood as multiple unless explicitly limited to a singular number.

[0142] It should be understood that, as used herein, the singular form "one" is intended to include the plural form as well, unless the context clearly supports an exception. It should also be understood that, as used herein, "and / or" refers to any and all possible combinations of one or more of the associated listed items.

[0143] Those skilled in the art should understand that the discussion of any of the above embodiments is merely exemplary and is not intended to imply that the scope of the invention (including the claims) is limited to these examples. Within the framework of the invention, technical features of the above embodiments or different embodiments can be combined, and many other variations of different aspects of the invention exist, which are not provided in the details for the sake of brevity. Therefore, any omissions, modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the invention should be included within the protection scope of the invention.

Claims

1. A method for detecting insulation condition, characterized in that, include: The discharge signal of the power module is acquired, and the discharge signal is subjected to high-pass filtering and wavelet noise reduction to obtain the discharge pulse; The morphological changes of bubbles were recorded at the three-way junction of the substrate, electrode, and silicon gel in the power module. Specifically, the three-dimensional contour of the bubble was obtained based on the instantaneous morphology of the bubble at the three-way junction of the substrate, electrode, and silicon gel in the power module, and the initial morphological data of the bubble was obtained. The changes of the bubble under the action of the electric field were continuously collected to obtain the time series morphological parameters and the corresponding images, and the fusion was used to obtain the evolutionary dataset of the morphological changes of the bubble. Based on phase-resolved partial discharge spectrum analysis of the discharge pulse, the changes in partial discharge parameters are obtained, and the changes in partial discharge parameters are classified to obtain insulation defect types; wherein, a feature vector set is constructed for each insulation defect type; the changes in partial discharge parameters are classified, and the similarity between the changes in partial discharge parameters and the feature vector set is calculated to obtain the insulation defect type corresponding to the feature vector with a similarity exceeding a threshold; The insulation degradation state is obtained by evaluating the morphological changes of the bubbles and the types of insulation defects. Specifically, a defect-bubble mapping relationship is established, and correlation is calculated to obtain the defect-bubble correlation. An insulation degradation state index is constructed based on the defect-bubble correlation, where the insulation degradation state index includes the remaining insulation life. The insulation degradation state state is then evaluated based on the insulation degradation state index to determine the morphological changes of the bubbles and the types of insulation defects.

2. The method for detecting insulation status according to claim 1, characterized in that, The steps of acquiring the discharge signal from the power module, performing high-pass filtering and wavelet noise reduction on the discharge signal to obtain the discharge pulse include: The discharge signal generated by the insulating medium of the power module under the action of an electric field is collected by a high-frequency sensor. Low-frequency noise was filtered out by a 400MHz high-pass filter, and the signal was decomposed into multiple scales by wavelet transform and high-frequency noise coefficients were removed to obtain the discharge pulse. The waveform of the discharge pulse is obtained by reconstructing the discharge pulse.

3. The method for detecting insulation status according to claim 2, characterized in that, The step of analyzing the discharge pulse based on phase-resolved partial discharge spectrum to obtain changes in partial discharge parameters includes: The discharge pulses are phase-marked, and the discharge pulses within each marked phase window are statistically analyzed to calculate the period, average discharge amplitude, and maximum discharge amplitude of each phase window. A two-dimensional PRPD spectrum is plotted with phase as the horizontal axis and discharge amplitude as the vertical axis. Feature parameters are extracted based on two-dimensional PRPD maps to obtain changes in partial discharge parameters, including the evolution of discharge phase, amplitude, and number of discharges over time.

4. The method for detecting insulation status according to claim 1, characterized in that, The morphological changes of the bubbles include an initial bubble-free stage, an isolated microbubble appearance stage, an elliptical bubble expansion stage, and a bubble penetration and breakdown stage.

5. A system for detecting insulation condition, characterized in that, include: The acquisition unit is configured to acquire the discharge signal of the power module, perform high-pass filtering and wavelet noise reduction on the discharge signal to obtain a discharge pulse; A bubble unit is configured to record the morphological changes of bubbles at the substrate-electrode-silica gel three-way junction of the power module. Specifically, based on the morphology of the bubble at the moment of bubble formation at the substrate-electrode-silica gel three-way junction of the power module, the three-dimensional contour of the bubble is obtained to obtain the initial morphological data of the bubble. The changes of the bubble under the action of an electric field are continuously collected to obtain time series morphological parameters and corresponding images, which are then fused to obtain an evolutionary dataset of the morphological changes of the bubble. The analysis unit is configured to analyze the discharge pulse based on the phase-resolved partial discharge spectrum, obtain changes in partial discharge parameters, classify the changes in partial discharge parameters, and obtain insulation defect types; wherein, a feature vector set is constructed for each insulation defect type; the changes in partial discharge parameters are classified, the similarity between the changes in partial discharge parameters 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. An evaluation unit is configured to evaluate the insulation degradation state based on the morphological changes of the bubbles and the type of insulation defects; wherein, a defect-bubble mapping relationship is established and correlation is calculated to obtain the defect-bubble correlation; an insulation degradation state index is constructed based on the defect-bubble correlation, wherein the insulation degradation state index includes the remaining insulation life; and the morphological changes of the bubbles and the type of insulation defects are evaluated based on the insulation degradation state index to obtain the insulation degradation state.

6. A computer device, comprising: At least one processor; And a memory storing a computer program executable on the processor, characterized in that the processor executes the program to perform the steps of a method for detecting insulation status as described in any one of claims 1 to 4.

7. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it performs the steps of the method for detecting insulation status as described in any one of claims 1 to 4.

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