A component anti-electromagnetic interference test method under complex working conditions

Abstract

This invention relates to the field of electromagnetic interference (EMI) testing technology, specifically to a method for testing the EMI immunity of electronic components under complex operating conditions. The method includes: acquiring partial discharge signals and mixed electromagnetic signals at various sensor locations of a monitoring reference component under test conditions; extracting EMI and PD signal components from the mixed electromagnetic signals; obtaining compensation parameters corresponding to each sensor location based on the fluctuation characteristics and location distribution of the partial discharge signals at different sensor locations of the monitoring reference component, and the fluctuation characteristics and location distribution of the PD signal components at different sensor locations of the monitoring reference component; using the compensation parameters to compensate and correct the partial discharge signals at each sensor location of the component under test; and judging the EMI immunity of the component under test based on the compensated and corrected signals and the corresponding EMI signal components. This invention improves the accuracy of EMI immunity test results for electronic components.

Description

Technical Field

[0001] This invention relates to the field of electromagnetic interference testing technology, and specifically to a method for testing the electromagnetic interference resistance of components under complex operating conditions. Background Technology

[0002] With the rapid development of industrial automation, new energy, and smart grids, key electronic components are operating in increasingly complex and harsh industrial environments. These environments generally present challenges from the coupling of multiple factors, including strong electromagnetic interference, extreme temperature and humidity changes, mechanical vibration, and chemical corrosion. Especially in application scenarios such as smart grids, hydropower networks, and new energy frequency converters, the complexity and intensity of the electromagnetic environment are constantly increasing, placing unprecedented demands on the reliability of components.

[0003] A series of electromagnetic compatibility (EMC) testing standards have been established. However, these traditional standards mainly focus on testing and evaluating single environmental factors and lack the ability to comprehensively simulate multi-physics coupled environments. In actual industrial scenarios, components often face the combined effects of sudden temperature changes, mechanical stress, and electromagnetic interference. This combined effect may cause the performance degradation of components to accelerate several times, and existing testing methods cannot accurately capture this complex degradation mechanism.

[0004] Current methods for testing the electromagnetic interference (EMI) immunity of electronic components can be mainly divided into three categories: laboratory testing, field monitoring, and simulation. Laboratory testing is typically conducted in a controlled electromagnetic environment, using various specialized equipment to generate specific electromagnetic field patterns to evaluate the EMI immunity performance of components. However, under complex operating conditions with a mixture of environmental factors, rapid heating may exacerbate partial discharge phenomena, affecting the accuracy of EMI testing. Although commonly used testing equipment with strong EMI immunity and optimized testing environments can improve testing accuracy, rapid heating can still cause high-frequency electromagnetic pulses generated by internal casing discharges, which overlap with external EMI signals, resulting in inaccurate interference testing and consequently lower accuracy of the EMI test results for components. Summary of the Invention

[0005] To address the issue of low accuracy in existing methods for testing the electromagnetic interference (EMI) immunity of electronic components, this invention aims to provide a method for testing EMI immunity of electronic components under complex operating conditions. The specific technical solution adopted is as follows:

[0006] This invention provides a method for testing the electromagnetic interference immunity of components under complex operating conditions, the method comprising the following steps:

[0007] Acquire partial discharge signals and mixed electromagnetic signals at the sensor locations of the reference component under test, as well as mixed electromagnetic signals at the sensor locations of the component under test.

[0008] EMI signal components and PD signal components are extracted from the mixed electromagnetic signal; a first distribution feature matrix is ​​obtained based on the fluctuation characteristics and position distribution of the partial discharge signals at different sensor locations of the monitoring reference component; a second distribution feature matrix is ​​obtained based on the fluctuation characteristics and position distribution of the PD signal components at different sensor locations of the monitoring reference component.

[0009] By combining the first distribution feature matrix and the second distribution feature matrix, compensation parameters corresponding to each sensor position are obtained; the compensation parameters are then used to compensate and correct the partial discharge signals at each sensor position of the device under test.

[0010] The electromagnetic interference immunity of the component under test is judged based on the compensated and corrected signal and the corresponding EMI signal components.

[0011] Preferably, the extraction of EMI signal components and PD signal components from the mixed electromagnetic signals includes:

[0012] Wavelet transform is performed on the hybrid electromagnetic signal to obtain the processed signal;

[0013] The processed signal is input into the trained adaptive filter LMS to obtain the EMI signal components;

[0014] The PD signal component is obtained by subtracting the EMI signal component from the processed signal.

[0015] Preferably, obtaining the first distribution feature matrix based on the fluctuation characteristics and location distribution of partial discharge signals at different sensor locations of the monitoring reference component includes:

[0016] For any sensor monitoring the reference component: based on the amplitude distribution of the partial discharge signal at the location of the sensor, obtain the first pulse amplitude; based on the relative position distribution between the sensor and the reference component, obtain the characteristic angle of the sensor.

[0017] A first distribution feature matrix is ​​constructed based on the first feature parameters of all sensors of the monitoring reference component. Each row of the first distribution feature matrix contains the first feature parameter of the same sensor, and each column contains the same first feature parameter. The first feature parameter includes feature angle, first pulse amplitude, first target rise time, first target fall time, first rise parameter, and first fall parameter.

[0018] The first target rise time is the duration of the rise phase before and adjacent to the maximum amplitude value in the partial discharge signal; the first target fall time is the duration of the fall phase after and adjacent to the maximum amplitude value in the partial discharge signal.

[0019] The first rising parameter is the average of the second derivatives of the signal during the rising phase before and adjacent to the maximum amplitude in the partial discharge signal; the first falling parameter is the average of the second derivatives of the signal during the falling phase after and adjacent to the maximum amplitude in the partial discharge signal.

[0020] Preferably, obtaining the first pulse amplitude based on the amplitude distribution of the partial discharge signal at any of the sensor locations includes: taking the maximum amplitude of the partial discharge signal at any of the sensor locations as the first pulse amplitude.

[0021] Preferably, obtaining the characteristic angle of any sensor based on the relative positional distribution of any sensor and the reference component includes: recording the direction from the reference component to the any sensor as the first direction of the any sensor; and taking the angle between the first direction and a preset direction as the characteristic angle of the any sensor.

[0022] Preferably, obtaining the second distribution feature matrix based on the fluctuation characteristics and positional distribution of PD signal components at different sensor locations of the monitoring reference component includes:

[0023] A second distributed feature matrix is ​​constructed based on the second feature parameters of all sensors of the monitoring reference component. Each row of the second distributed feature matrix contains the second feature parameters of the same sensor, and each column contains the same type of second feature parameter. The second feature parameters include feature angle, second pulse amplitude, second target rise time, second target fall time, second rise parameter, and second fall parameter.

[0024] The second target rise time is the duration of the rise phase before and adjacent to the maximum amplitude in the PD signal component; the second target fall time is the duration of the fall phase after and adjacent to the maximum amplitude in the PD signal component.

[0025] The second rising parameter is the average of the second derivatives of the signal during the rising phase before and adjacent to the maximum amplitude in the PD signal component; the second falling parameter is the average of the second derivatives of the signal during the falling phase after and adjacent to the maximum amplitude in the PD signal component.

[0026] Preferably, the acquisition of the second pulse amplitude includes: for any sensor of the monitoring reference component, taking the maximum amplitude of the PD signal component at the location of the any sensor as the second pulse amplitude.

[0027] Preferably, the step of combining the first distribution feature matrix and the second distribution feature matrix to obtain the compensation parameters corresponding to each sensor position includes:

[0028] The difference between the second distribution feature matrix and the first distribution feature matrix is ​​calculated to obtain the compensation parameters corresponding to each sensor position.

[0029] Preferably, the step of compensating and correcting the partial discharge signals at each sensor location of the monitored component under test using the compensation parameters includes:

[0030] The partial discharge signals at each sensor location of the monitored component under test are decomposed, the fluctuation signals are extracted, and the rising and falling curves of the fluctuation signals are refitted using the compensation parameters and fused to obtain the compensated and corrected signal.

[0031] Preferably, the step of judging the electromagnetic interference immunity of the component under test based on the compensated and corrected signal and the corresponding EMI signal components includes:

[0032] The test levels of radiated radio frequency electromagnetic field immunity are classified according to the components of EMI signals.

[0033] The apparent charge of the decomposed pulse is obtained based on the compensated and corrected signal and the corresponding test level.

[0034] By comparing the apparent charge with a preset threshold, the electromagnetic interference immunity of the component under test can be determined.

[0035] The present invention has at least the following beneficial effects:

[0036] This invention first extracts the EMI and PD signal components from the mixed electromagnetic signal based on their signal characteristics. Then, it analyzes the fluctuation characteristics and location distribution of partial discharge signals at different sensor locations of the monitoring reference component, as well as the fluctuation characteristics and location distribution of the PD signal components at different sensor locations. Since the interference experienced by different sensor locations during signal acquisition may vary, compensation parameters corresponding to each sensor location are determined by combining the first and second distribution feature matrices. This allows for different degrees of compensation and correction of the partial discharge signals at different sensor locations of the monitored component under test. Based on the compensated and corrected signals and the corresponding EMI signal components, the electromagnetic interference immunity of the component under test is assessed. The method provided by this invention improves the accuracy of electromagnetic interference immunity test results, enabling the selection of highly reliable and strong anti-interference components, enhancing the stability and lifespan of the entire electronic system in complex environments, and providing a basis for key component selection in fields such as industrial automation, smart grids, and new energy. Attached Figure Description

[0037] To more clearly illustrate the technical solutions and advantages 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 drawings can be obtained based on these drawings without creative effort.

[0038] Figure 1 This is a flowchart of a method for testing the electromagnetic interference resistance of components under complex operating conditions, provided in an embodiment of the present invention. Detailed Implementation

[0039] To further illustrate the technical means and effects adopted by the present invention to achieve the intended purpose, the following detailed description, in conjunction with the accompanying drawings and preferred embodiments, describes a method for testing the electromagnetic interference resistance of components under complex working conditions according to the present invention.

[0040] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0041] The following description, in conjunction with the accompanying drawings, details the specific scheme of the electromagnetic interference resistance testing method for components under complex working conditions provided by the present invention.

[0042] An example of a method for testing the electromagnetic interference immunity of components under complex operating conditions:

[0043] This embodiment proposes a method for testing the electromagnetic interference immunity of components under complex operating conditions, such as... Figure 1 As shown, a component electromagnetic interference immunity testing method under complex operating conditions in this embodiment includes the following steps:

[0044] Step S1: Acquire the partial discharge signal and mixed electromagnetic signal of each sensor position of the reference component under test, and the mixed electromagnetic signal of each sensor position of the component under test.

[0045] In order to simulate the complex working conditions of the components, this embodiment will first set up a test field for the components. The test field should have the following functions: (1) Temperature control: it can achieve rapid heating, such as heating more than 10°C per minute and alternating damp heat cycle; (2) Electromagnetic environment: it can apply electromagnetic interference of controllable strength, such as generating EMI of a specific frequency band through an antenna or coil; (3) Vibration simulation: a vibration table can be selected to simulate the mechanical vibration environment; (4) Shielding and grounding: the test room should have a good electromagnetic shielding and grounding system to avoid external interference. Then, the components are fixed on an insulating frame to avoid contact with metal and thus introduce additional interference; an infrared heater or a high-power resistive heating element is used as a temperature control device to realize the heating temperature control of the components, thereby simulating the rapid heating of complex working conditions; a standard EMI antenna or coil is used and arranged around the components to generate a controllable electromagnetic field to simulate electromagnetic interference under complex working conditions; the frequency range of the coil covers the typical industrial interference frequency band. A high-voltage pulse generator or point electromagnetic source is used, positioned near the components, to simulate partial discharge signals in the casing under complex operating conditions. Multiple magnetic field sensors are placed at different locations around the components to collect mixed electromagnetic signals. It should be noted that all the above devices are fixed using non-magnetic clamps to avoid electromagnetic interference. The total number and placement of the magnetic field sensors are determined by the implementer based on specific circumstances, and will not be elaborated further here.

[0046] After the experimental field was set up, experimental data was collected. Specifically, all noise sources were turned off, and the initial temperature of the temperature control system was set to 25°C. The temperature control system was started, and the temperature was increased at the set rate. An EMI electromagnetic interference source was activated to apply an electromagnetic interference signal. A PD simulation device was activated to generate intermittent or continuous partial discharge. Data was collected through the aforementioned sensors and connected to a high-speed oscilloscope or spectrum analyzer to acquire mixed electromagnetic signals. After a certain period of time, the EMI electromagnetic interference source was turned off, leaving only the PD simulation signal source, and signal acquisition continued to obtain a pure partial discharge signal. It should be noted that partial discharge signals and mixed electromagnetic signals were collected at each magnetic field sensor location. It should also be noted that in this embodiment, partial discharge signals and mixed electromagnetic signals at each sensor location monitoring the reference component, and mixed electromagnetic signals at each sensor location monitoring the component under test, were collected. When collecting partial discharge signals and mixed electromagnetic signals at each sensor location monitoring the reference component, the component placed in the experimental field was the reference component; when testing the component under test, the component placed was the component under test.

[0047] Thus far, this embodiment has collected partial discharge signals and mixed electromagnetic signals at the sensor locations of the reference component, as well as mixed electromagnetic signals at the sensor locations of the component under test.

[0048] Step S2: Extract EMI signal components and PD signal components from the mixed electromagnetic signals; obtain a first distribution feature matrix based on the fluctuation characteristics and position distribution of partial discharge signals at different sensor locations of the monitoring reference component; obtain a second distribution feature matrix based on the fluctuation characteristics and position distribution of PD signal components at different sensor locations of the monitoring reference component.

[0049] Partial discharge signals have an extremely wide spectral range, extending from a few megahertz to several gigahertz. External electromagnetic interference (EMI) signals in the experimental field also have a wide spectral range, with their core interference frequency band concentrated in the range of several hundred kilohertz to several hundred megahertz. Therefore, under complex operating conditions, rapid temperature rise exacerbates partial discharge phenomena, leading to overlap and coupling between partial discharge and EMI signals during component electromagnetic interference immunity testing, thus affecting the accuracy of electromagnetic field tests.

[0050] The purpose of electromagnetic interference (EMI) immunity testing on electronic components is to determine whether the component can operate normally in an external EMI environment. However, when a component generates partial discharge signals under complex operating conditions, these signals overlap and couple with external EMI signals, leading to errors in the assessment of external EMI and thus affecting the determination of the component's EMI immunity. Therefore, by decomposing the partial discharge signal from the mixed electromagnetic signal, we can better measure the actual test environment and external interference of the component during EMI immunity testing, thereby improving the accuracy and stability of EMI immunity testing under complex operating conditions.

[0051] To obtain more accurate electromagnetic interference (EMI) test results for components, it is first necessary to separate the partial discharge (PD) signal component and the EMI signal component from the mixed electromagnetic signal. In the processed signal obtained above, in addition to partial discharge and EMI signals, there may also be other channel noise; therefore, this noise needs to be eliminated first.

[0052] Because wavelet transform has multi-resolution analysis characteristics, it can effectively capture the transient pulse characteristics of PD (Power Probe) and suppress broadband EMI noise and other channel noise. Therefore, wavelet transform is used for noise cancellation, and DB4 is chosen as the wavelet basis. The processed mixed electromagnetic signal is subjected to wavelet transform to obtain the processed signal. The processed signal eliminates significant noise, and the mixed signal can be considered as a superposition of PD and EMI signals. Therefore, the PD and EMI signals need to be decomposed in the processed signal. Since the PD signal is unstable and pulsed, while the EMI signal is continuous and relatively stable, the PD signal is considered noise, and the processed signal is used as the expected signal. This signal is input into the trained adaptive filter LMS, and the EMI signal component is output. The training process of the adaptive filter LMS is a prior art technique, and training continues until the adaptive filter LMS reaches weight convergence; this embodiment will not elaborate further.

[0053] The EMI signal component is subtracted from the processed signal to obtain the PD signal component. Thus, the mixed signal has been decomposed using wavelet transform and adaptive filtering, yielding both the EMI and PD signal components.

[0054] Under complex operating conditions, when components generate partial discharge due to rapid heating and electromagnetic interference (EMI), mutual impedance coupling occurs between the EMI source and the partial discharge source, leading to waveform distortion in both the EMI and partial discharge signals. Furthermore, since the signal decomposition process described above treats the processed signal as the expected signal, the aforementioned waveform distortion is concentrated in the partial discharge signal, resulting in further distortion of the partial discharge signal waveform.

[0055] Partial discharge (PD) signals are transient current pulses generated by minute breakdowns within an insulating medium. They are characterized by high frequency and anisotropy in the radiation field direction. Therefore, the anisotropy of the signal can be collected by multiple magnetic field sensors arranged as described above, allowing for analysis of the waveform characteristics of the PD signal. Then, distortion analysis and compensation are performed by combining the PD signal components obtained from the above decomposition.

[0056] Since partial discharge signals are generated by minute breakdowns within an insulating medium, where current pulses break down along a specific direction within the medium, forming dipoles, the radiated electromagnetic field exhibits strong directionality in space. This directionality is primarily reflected in the signal's time-domain waveform.

[0057] Because the high-frequency components attenuate differently in different directions, the sensor's orientation not only affects the amplitude but also the specific waveform received, causing changes in the rise and fall times of the pulse, and consequently, changes in the specific waveform.

[0058] Based on the above characteristics, for any sensor monitoring the reference component: the maximum amplitude of the partial discharge signal at the sensor location is taken as the first pulse amplitude. The direction from the reference component to the sensor is recorded as the first direction of the sensor; the angle between the first direction and a preset direction is taken as the characteristic angle of the sensor. In this embodiment, the preset direction is horizontal to the right. Using the above method, the characteristic angle of each sensor monitoring the reference component can be obtained.

[0059] A first distribution feature matrix is ​​constructed based on the first characteristic parameters of all sensors of the monitoring reference component. That is, the elements in the first distribution feature matrix are the first characteristic parameters. Each row of the first distribution feature matrix represents the first characteristic parameter of the same sensor, and each column represents the same first characteristic parameter. The first characteristic parameters include characteristic angle, first pulse amplitude, first target rise time, first target fall time, first rise parameter, and first fall parameter. The number of rows in the first distribution feature matrix is ​​equal to the number of sensors in the monitoring reference component, and the number of columns in the first distribution feature matrix is ​​6. In this embodiment, the columns, from left to right, are characteristic angle, first pulse amplitude, first target rise time, first target fall time, first rise parameter, and first fall parameter.

[0060] Wherein, the first target rise time is the duration of the rise phase preceding and adjacent to the maximum amplitude in the partial discharge signal; the first target fall time is the duration of the fall phase following and adjacent to the maximum amplitude in the partial discharge signal; the first rise parameter is the average of the second derivatives of the signal during the rise phase preceding and adjacent to the maximum amplitude in the partial discharge signal; and the first fall parameter is the average of the second derivatives of the signal during the fall phase following and adjacent to the maximum amplitude in the partial discharge signal. It should be noted that the second derivative is used to represent the rate of change of amplitude.

[0061] For any sensor monitoring the reference component, the maximum amplitude of the PD signal component at that sensor location is taken as the second pulse amplitude. Each sensor has a corresponding second pulse amplitude.

[0062] A second distribution feature matrix is ​​constructed based on the second feature parameters of all sensors of the monitoring reference components. Each row of the second distribution feature matrix contains the second feature parameters of the same sensor, and each column contains the same type of second feature parameter. The second feature parameters include feature angle, second pulse amplitude, second target rise time, second target fall time, second rise parameter, and second fall parameter.

[0063] Wherein, the second target rise time is the duration of the rise phase before and adjacent to the maximum amplitude in the PD signal component; the second target fall time is the duration of the fall phase after and adjacent to the maximum amplitude in the PD signal component; the second rise parameter is the average of the second derivatives of the signal during the rise phase before and adjacent to the maximum amplitude in the PD signal component; and the second fall parameter is the average of the second derivatives of the signal during the fall phase after and adjacent to the maximum amplitude in the PD signal component. Since the second distribution feature matrix is ​​derived from the mixed signal decomposition, it includes the waveform distortion characteristics of the PD signal.

[0064] It should be noted that the second distribution feature matrix and the first distribution feature matrix represent the parameters of the same sensor in the same row. The number of rows in the second distribution feature matrix is ​​equal to the number of sensors in the monitoring reference components, and the number of columns in the second distribution feature matrix is ​​6. In this embodiment, in the order from left to right, they are the characteristic angle, the second pulse amplitude, the second target rise time, the second target fall time, the second rise parameter, and the second fall parameter.

[0065] Thus, this embodiment has obtained the first distribution feature matrix and the second distribution feature matrix.

[0066] Step S3: Combine the first distribution feature matrix and the second distribution feature matrix to obtain the compensation parameters corresponding to each sensor position; use the compensation parameters to compensate and correct the partial discharge signals of each sensor position of the device under test.

[0067] In this embodiment, the first distribution feature matrix and the second distribution feature matrix are obtained in the above steps. Next, the difference between the second distribution feature matrix and the first distribution feature matrix is ​​calculated to obtain the compensation parameters corresponding to each sensor position.

[0068] Furthermore, empirical mode decomposition (EMD) is performed on the partial discharge signals at each sensor location of the device under test to extract the fluctuation signals. The rising and falling curves of the fluctuation signals are then refitted using compensation parameters, and the fitting results are fused to obtain the compensated and corrected signal. Empirical mode decomposition is an existing technique and will not be elaborated upon further here.

[0069] Thus, the method provided in this embodiment has been used to complete the compensation and correction of the partial discharge signals at each sensor location of the device under test.

[0070] Step S4: Determine the electromagnetic interference immunity of the component under test based on the compensated and corrected signal and the corresponding EMI signal components.

[0071] In this embodiment, the partial discharge signals at each sensor location are compensated and corrected in the above steps to obtain the compensated and corrected signals. Next, the electromagnetic interference immunity of the device under test will be judged based on the compensated and corrected signals and the EMI signal components corresponding to each sensor location of the device under test.

[0072] Specifically, the test levels for radiated radio frequency electromagnetic field immunity are classified according to the components of the EMI signal; the apparent charge of the decomposed pulse is obtained based on the compensated and corrected signal and the corresponding test level; an immunity threshold is set, and then the electromagnetic interference immunity of the component under test is judged by comparing the apparent charge with the preset threshold. This process is existing technology and will not be described in detail in this embodiment. The above-mentioned judgment results of the electromagnetic interference immunity of the component under test are summarized and statistically analyzed, and components with complex operating conditions are entered into a safe and reliable component library to provide data support for component selection in hardware design.

[0073] Thus, the method provided in this embodiment has been used to complete the testing of the electromagnetic interference immunity of the components.

[0074] This embodiment first extracts the EMI and PD signal components from the mixed electromagnetic signal based on their signal characteristics. Then, it analyzes the fluctuation characteristics and location distribution of the partial discharge signal at different sensor locations of the monitoring reference component, as well as the fluctuation characteristics and location distribution of the PD signal component at different sensor locations of the monitoring reference component. Since the interference experienced by different sensor locations during signal acquisition may vary, compensation parameters corresponding to each sensor location are determined by combining the first and second distribution feature matrices. This allows for different degrees of compensation and correction of the partial discharge signals at different sensor locations of the monitored component under test. Based on the compensated and corrected signals and the corresponding EMI signal components, the electromagnetic interference immunity of the component under test is assessed. The method provided in this embodiment improves the accuracy of the electromagnetic interference immunity test results of the component under test, enabling the selection of components with high reliability and strong anti-interference capabilities. This enhances the stability and lifespan of the entire electronic system in complex environments, providing a basis for key component selection in fields such as industrial automation, smart grids, and new energy.

[0075] It should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for testing the electromagnetic interference immunity of components under complex operating conditions, characterized in that, The method includes the following steps: Acquire partial discharge signals and mixed electromagnetic signals at the sensor locations of the reference component under test, as well as mixed electromagnetic signals at the sensor locations of the component under test. EMI signal components and PD signal components are extracted from the mixed electromagnetic signal; a first distribution feature matrix is ​​obtained based on the fluctuation characteristics and position distribution of the partial discharge signals at different sensor locations of the monitoring reference component; a second distribution feature matrix is ​​obtained based on the fluctuation characteristics and position distribution of the PD signal components at different sensor locations of the monitoring reference component. By combining the first distribution feature matrix and the second distribution feature matrix, compensation parameters corresponding to each sensor position are obtained; the compensation parameters are then used to compensate and correct the PD signal components at each sensor position of the device under test. The electromagnetic interference immunity of the component under test is judged based on the compensated and corrected signal and the corresponding EMI signal components.

2. The method for testing the electromagnetic interference immunity of components under complex operating conditions according to claim 1, characterized in that, The extraction of EMI signal components and PD signal components from the mixed electromagnetic signals includes: Wavelet transform is performed on the hybrid electromagnetic signal to obtain the processed signal; The processed signal is input into the trained adaptive filter LMS to obtain the EMI signal components; The PD signal component is obtained by subtracting the EMI signal component from the processed signal.

3. The method for testing the electromagnetic interference immunity of components under complex operating conditions according to claim 1, characterized in that, The first distribution feature matrix is ​​obtained based on the fluctuation characteristics and location distribution of partial discharge signals at different sensor locations of the monitoring reference component, including: For any sensor monitoring the reference component: based on the amplitude distribution of the partial discharge signal at the location of the sensor, obtain the first pulse amplitude; based on the relative position distribution between the sensor and the reference component, obtain the characteristic angle of the sensor. A first distribution feature matrix is ​​constructed based on the first feature parameters of all sensors of the monitoring reference component. Each row of the first distribution feature matrix contains the first feature parameter of the same sensor, and each column contains the same first feature parameter. The first feature parameter includes feature angle, first pulse amplitude, first target rise time, first target fall time, first rise parameter, and first fall parameter. The first target rise time is the duration of the rise phase before and adjacent to the maximum amplitude value in the partial discharge signal; the first target fall time is the duration of the fall phase after and adjacent to the maximum amplitude value in the partial discharge signal. The first rising parameter is the average of the second derivatives of the signal during the rising phase before and adjacent to the maximum amplitude in the partial discharge signal; the first falling parameter is the average of the second derivatives of the signal during the falling phase after and adjacent to the maximum amplitude in the partial discharge signal.

4. The method for testing the electromagnetic interference immunity of components under complex operating conditions according to claim 3, characterized in that, Obtaining the first pulse amplitude based on the amplitude distribution of the partial discharge signal at any of the sensor locations includes: taking the maximum amplitude of the partial discharge signal at any of the sensor locations as the first pulse amplitude.

5. The method for testing the electromagnetic interference immunity of components under complex operating conditions according to claim 3, characterized in that, The step of obtaining the characteristic angle of any sensor based on the relative position distribution of any sensor and the reference component includes: recording the direction from the reference component to the any sensor as the first direction of the any sensor; and taking the angle between the first direction and the preset direction as the characteristic angle of the any sensor.

6. The method for testing the electromagnetic interference immunity of components under complex operating conditions according to claim 1, characterized in that, The second distribution feature matrix is ​​obtained based on the fluctuation characteristics and positional distribution of PD signal components at different sensor locations of the monitoring reference component, including: A second distributed feature matrix is ​​constructed based on the second feature parameters of all sensors of the monitoring reference component. Each row of the second distributed feature matrix contains the second feature parameters of the same sensor, and each column contains the same type of second feature parameter. The second feature parameters include feature angle, second pulse amplitude, second target rise time, second target fall time, second rise parameter, and second fall parameter. The second target rise time is the duration of the rise phase before and adjacent to the maximum amplitude in the PD signal component; the second target fall time is the duration of the fall phase after and adjacent to the maximum amplitude in the PD signal component. The second rising parameter is the average of the second derivatives of the signal during the rising phase before and adjacent to the maximum amplitude in the PD signal component; the second falling parameter is the average of the second derivatives of the signal during the falling phase after and adjacent to the maximum amplitude in the PD signal component.

7. The method for testing the electromagnetic interference immunity of components under complex operating conditions according to claim 6, characterized in that, The acquisition of the second pulse amplitude includes: for any sensor of the monitoring reference component, taking the maximum amplitude of the PD signal component at the location of the any sensor as the second pulse amplitude.

8. The method for testing the electromagnetic interference immunity of components under complex operating conditions according to claim 1, characterized in that, The step of combining the first distribution feature matrix and the second distribution feature matrix to obtain the compensation parameters corresponding to each sensor position includes: The difference between the second distribution feature matrix and the first distribution feature matrix is ​​calculated to obtain the compensation parameters corresponding to each sensor position.

9. The method for testing the electromagnetic interference immunity of components under complex operating conditions according to claim 1, characterized in that, The step of compensating and correcting the PD signal components at each sensor position of the monitored component under test using the compensation parameters includes: The PD signal components at each sensor location of the device under test are decomposed, the fluctuation signal is extracted, and the rising and falling curves of the fluctuation signal are refitted using the compensation parameters and fused to obtain the compensated and corrected signal.

10. The method for testing the electromagnetic interference immunity of components under complex operating conditions according to claim 1, characterized in that, The determination of the electromagnetic interference immunity of the component under test based on the compensated and corrected signal and the corresponding EMI signal components includes: The test levels of radiated radio frequency electromagnetic field immunity are classified according to the components of EMI signals. The apparent charge of the decomposed pulse is obtained based on the compensated and corrected signal and the corresponding test level. By comparing the apparent charge with a preset threshold, the electromagnetic interference immunity of the component under test can be determined.

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