Method, device and electronic equipment for testing electronic components

Abstract

The present disclosure provides a method and device for testing an electronic device, and an electronic device. The method comprises: inputting a first detection signal to an initial system, and obtaining a first output signal generated by the initial system; determining a first signal feature based on the first output signal; inputting a second detection signal to a target system, and obtaining a second output signal generated by the target system; the target system is formed by connecting the initial system and a device under test; determining a target signal feature based on the second output signal; determining a partial discharge signal in the second output signal based on the first signal feature and the target signal feature; and determining a test result of the device under test based on the first output signal and the partial discharge signal. In the process of testing the electronic device, the partial discharge signal generated by the device under test is determined through morphology and noise characteristics, which improves the detection accuracy of the partial discharge signal and the accuracy of the analysis result of the performance of the electronic device.

Description

TECHNICAL FIELD

[0001] The present disclosure relates to the field of electronic device processing, and in particular, to a test method and device for an electronic device and an electronic device. BACKGROUND

[0002] In the reliability evaluation of high-voltage power electronic devices, partial discharge (PD) detection is one of the key diagnostic methods. Partial discharge signals are usually used to determine the location and development trend of insulation defects, and the accuracy of identification directly relates to the safety and reliability of device operation. In order to simulate the working state of power electronic devices in the power system, a fast rising square wave voltage can be used as an excitation source for partial discharge detection to approach the discharge environment under working conditions. Under square wave excitation, there are a large number of environmental noise signals, and in scenarios where voltage mutations are easy to occur, the detection process is also accompanied by common-mode current introduced by the voltage mutation generation system, making the detection result of square wave voltage partial discharge less accurate.

[0003] In related technologies, based on covariance matrix eigenvalue distribution analysis, signal features can be extracted through eigenvalue interval division and amplitude transformation to further determine signals generated by partial discharge. However, this method is difficult to extract partial discharge signals that are highly overlapped with noise spectrum in complex electromagnetic environments. In practical applications, multi-dimensional features in time and frequency domains can be combined to automatically classify signals using clustering algorithms to identify signals generated by partial discharge. However, in scenarios where voltage mutations are easy to occur, the common-mode noise under signals generated by voltage mutations is synchronized with the switching speed, and partial discharge signals are also mixed in, making it difficult to accurately detect signals generated by partial discharge, and the accuracy of detection is low. SUMMARY

[0004] Therefore, the purpose of the present disclosure is to provide a test method and device for an electronic device to improve the detection accuracy of partial discharge signals and improve the accuracy of performance analysis results of the electronic device during the test of the electronic device.

[0005] In a first aspect, an embodiment of the present disclosure provides a test method for an electronic device, the method comprising: inputting a first detection signal to an initial system and obtaining a first output signal generated by the initial system; determining a first signal feature based on the first output signal; inputting a second detection signal to a target system and obtaining a second output signal generated by the target system; the target system being formed by connecting the initial system and a device under test; the signal parameters of the second detection signal being consistent with those of the first detection signal; determining a target signal form feature based on the second output signal; determining a partial discharge signal in the second output signal based on the first signal feature and the target signal form feature; and determining a test result of the device under test based on the first output signal and the partial discharge signal.

[0006] The first detection signal mentioned above includes a first square wave signal; the first output signal is generated by the initial system under the action of the first square wave signal; the step of determining the first signal characteristics based on the first output signal includes: calculating the first signal characteristics based on the definition of pulse signal and relative entropy in the first output signal.

[0007] The second detection signal mentioned above includes a second square wave signal; the second output signal is generated by the target system under the action of the second square wave; before determining the target signal morphological characteristics based on the second output signal, the method further includes: determining whether the second output signal includes a pulse signal with an amplitude greater than or equal to a specified amplitude; if not, increasing the voltage of the second square wave signal; inputting the voltage-increased second square wave signal to the target system and acquiring the third output signal generated by the target system; determining whether the third output signal includes a pulse signal with an amplitude greater than or equal to a specified amplitude; if so, updating the second output signal to the third output signal.

[0008] The second detection signal mentioned above includes a second square wave signal; the second output signal is generated by the target system under the action of the second square wave signal; the step of determining the target signal morphological characteristics based on the second output signal includes: identifying a pulse signal in the second output signal; determining a target pulse signal from the identified pulse signal; and determining the target signal morphological characteristics based on the target pulse signal.

[0009] The above-mentioned step of determining the target pulse signal from the identified pulse signals includes: determining the pulse signal generated during the voltage stabilization phase of the second square wave signal from the identified pulse signals; and determining the target pulse signal from the determined pulse signals.

[0010] The above-mentioned step of determining the target pulse signal from the determined pulse signals includes: determining the pulse signal with the largest amplitude among the determined pulse signals as the target pulse signal.

[0011] The aforementioned target signal morphological characteristics include at least the following information: the pulse width, amplitude, and waveform asymmetry of the target pulse signal.

[0012] The second detection signal mentioned above includes a second square wave signal; the second output signal includes a target pulse signal generated by the initial system under the action of the second square wave signal; the step of determining the partial discharge signal in the second output signal based on the first signal characteristics and the target signal morphology characteristics includes: for each target pulse signal in the second output signal, determining the similarity between the signal morphology characteristics of the target pulse signal and the target signal morphology characteristics; and determining whether the target pulse signal is a partial discharge signal based on the similarity, the first signal characteristics, and the voltage change state of the second square wave signal corresponding to the target pulse signal.

[0013] The steps for determining whether a target pulse signal is a partial discharge signal based on similarity, first signal characteristics, and the voltage change state of the second square wave signal corresponding to the target pulse signal include: if the similarity is greater than or equal to a preset similarity threshold, determining whether the target pulse signal is at the rising or falling edge of the second square wave signal; if not, determining the target pulse signal as a partial discharge signal; if so, determining whether the target pulse signal is a partial discharge signal based on the first signal characteristics.

[0014] The first signal feature is determined based on the definition of the first output signal and relative entropy. The step of determining whether the target pulse signal is a partial discharge signal based on the first signal feature includes: calculating the relative entropy result between the target pulse signal and the first output signal based on the first signal feature; if the relative entropy result is greater than or equal to a preset threshold, the target pulse signal is determined to be a partial discharge signal.

[0015] The first detection signal includes a first square wave signal; the first output signal includes a first pulse signal generated by the initial system under the action of the first square wave signal; the second detection signal includes a second square wave signal; the second output signal includes a second pulse signal generated by the target system under the action of the second square wave signal; the step of determining the test result of the device under test based on the first output signal and the partial discharge signal includes: determining the Weibull distribution parameters of the partial discharge signal based on the first pulse signal and the partial discharge signal; and determining the test result of the device under test based on the Weibull distribution parameters.

[0016] The aforementioned Weibull distribution parameters include probability density distribution parameters and cumulative distribution parameters; the probability density distribution parameters are used to indicate the correspondence between the intensity and frequency of the partial discharge signal and the first pulse signal when they are generated; the cumulative distribution parameters are used to indicate the distribution trend of the partial discharge signal and the first pulse signal.

[0017] The above method also includes: determining whether the Weibull distribution parameters meet the preset parameter distribution range; if they do, determining that the test results are reliable.

[0018] Secondly, embodiments of this disclosure provide a testing apparatus for electronic devices, the apparatus comprising: a first signal acquisition module, configured to input a first detection signal to an initial system and acquire a first output signal generated by the initial system; a first signal feature determination module, configured to determine a first signal feature based on the first output signal; a second signal acquisition module, configured to input a second detection signal to a target system and acquire a second output signal generated by the target system; the target system is formed by connecting the initial system and the device under test; the signal parameters of the second detection signal are consistent with those of the first detection signal; a signal morphology feature determination module, configured to determine a target signal morphology feature based on the second output signal; a partial discharge signal determination module, configured to determine a partial discharge signal in the second output signal based on the first signal feature and the target signal morphology feature; and a test result determination module, configured to determine the test result of the device under test based on the first output signal and the partial discharge signal.

[0019] Thirdly, embodiments of this disclosure provide an electronic device, including a processor and a memory, wherein the memory stores machine-executable instructions that can be executed by the processor, and the processor executes the machine-executable instructions to implement the above-described testing method for the electronic device.

[0020] Fourthly, embodiments of this disclosure provide a machine-readable storage medium storing machine-executable instructions. When the machine-executable instructions are invoked and executed by a processor, the machine-executable instructions cause the processor to implement the above-described testing method for electronic devices.

[0021] The embodiments disclosed herein bring the following beneficial effects:

[0022] The above provides a testing method, apparatus, and electronic device for electronic devices. The method includes: inputting a first detection signal to an initial system and acquiring a first output signal generated by the initial system; determining a first signal characteristic based on the first output signal; inputting a second detection signal to a target system and acquiring a second output signal generated by the target system; the target system is formed by connecting the initial system and the device under test (DUT); the signal parameters of the second detection signal are consistent with those of the first detection signal; determining the morphological characteristics of the target signal based on the second output signal; determining a partial discharge signal in the second output signal based on the first signal characteristic and the morphological characteristics of the target signal; and determining the test result of the DUT based on the first output signal and the partial discharge signal. This method, during the testing of electronic devices, determines the partial discharge signal generated by the DUT through morphological and noise characteristics, improving the accuracy of partial discharge signal detection and thus improving the accuracy of the analysis results of the electronic device's performance.

[0023] Other features and advantages of this disclosure will be set forth in the following description and will be apparent in part from the description or may be learned by practicing the disclosure. The objects and other advantages of this disclosure are realized and obtained through the structures particularly pointed out in the description, claims and drawings.

[0024] To make the above-mentioned objects, features and advantages of this disclosure more apparent and understandable, preferred embodiments are described below in detail with reference to the accompanying drawings. Attached Figure Description

[0025] To more clearly illustrate the technical solutions in the specific embodiments of this disclosure or the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this disclosure. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0026] Figure 1 A flowchart illustrating a testing method for an electronic device provided in this disclosure embodiment;

[0027] Figure 2 A schematic diagram illustrating a testing process for an electronic device provided in an embodiment of this disclosure;

[0028] Figure 3 A schematic diagram of a square wave signal and a detection signal provided in an embodiment of this disclosure;

[0029] Figure 4 A schematic diagram of another square wave signal and detection signal provided in an embodiment of this disclosure;

[0030] Figure 5 This is a schematic diagram of a second detection signal provided in an embodiment of the present disclosure;

[0031] Figure 6 This is a schematic diagram of another second detection signal provided in an embodiment of the present disclosure;

[0032] Figure 7 A schematic diagram of a partial discharge signal provided in an embodiment of this disclosure;

[0033] Figure 8 A schematic diagram of a noise signal provided in an embodiment of this disclosure;

[0034] Figure 9 A schematic diagram of a Weibull probability density distribution provided in an embodiment of this disclosure;

[0035] Figure 10 This is a schematic diagram of another Weibull probability density distribution provided in an embodiment of the present disclosure;

[0036] Figure 11 A schematic diagram of a Weibull cumulative distribution provided in an embodiment of this disclosure;

[0037] Figure 12 Another schematic diagram of the Weibull cumulative distribution provided in this embodiment of the disclosure;

[0038] Figure 13 A schematic diagram of the structure of a testing apparatus for an electronic device provided in an embodiment of this disclosure;

[0039] Figure 14 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this disclosure. Detailed Implementation

[0040] To make the objectives, technical solutions, and advantages of the embodiments of this disclosure clearer, the technical solutions of this disclosure will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this disclosure, and not all embodiments. Based on the embodiments of this disclosure, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this disclosure.

[0041] In the reliability assessment of high-voltage power electronic devices, partial discharge detection is one of the key diagnostic methods. Partial discharge signals are commonly used to determine the location and development trend of insulation defects, and the accuracy of their identification directly affects the safety and reliability of equipment operation. In practical applications, to simulate operating conditions, an increasing number of tests use square wave voltages with fast rise times as the excitation source; for example, square wave voltages with repetitive frequencies above several kHz and dv / dt > 1 kV / μs can be used. However, square wave excitation is accompanied by a large amount of noise signals, such as electromagnetic interference, sensor coupling interference, and equipment background signals, making the accurate differentiation between partial discharge signals and noise signals a significant challenge.

[0042] In related technologies, methods for distinguishing partial discharge (PD) signals from noise signals mainly focus on the background of sinusoidal or DC voltages, while there is currently no method for identifying partial discharge signals under high dv / dt square wave voltages. In actual operation, high-voltage power electronic devices undergo thousands or more switching frequencies per second under high dv / dt square waves. Each switching operation easily generates partial discharge signals in the square wave signal, causing damage far greater than that of sinusoidal or DC voltages. Furthermore, the common-mode current generated by high dv / dt makes extracting partial discharge signals under square wave signals even more difficult. Without the ability to distinguish between the two types of signals, it is impossible to construct a dataset, rendering previous reference methods inapplicable. Therefore, effectively distinguishing partial discharge signals from noise signals under high dv / dt square waves plays a crucial role in ensuring the reliability of high-voltage power electronic devices.

[0043] In related technologies, partial discharge signals can be identified by analyzing the distribution of eigenvalues ​​of the covariance matrix, dividing the eigenvalue intervals, and extracting signal features through amplitude transformation. However, this discrimination criterion relies on a single threshold, which cannot distinguish partial discharge signals that highly overlap with noise spectra in complex electromagnetic environments, such as the superposition of common-mode noise and partial discharge signals in high dv / dt square waves. Therefore, it is not suitable for noise identification of square wave signals.

[0044] In related technologies, multi-dimensional features in the time and frequency domains can be combined to automatically classify signals using clustering algorithms, reducing manual intervention. Furthermore, the clustering results can be visually displayed using PRPD charts, facilitating analysis. For example, in the time domain, arithmetic coding can preserve waveform information, while in the frequency domain, amplitude distribution can be analyzed using Fast Fourier Transform (FFT).

[0045] However, common-mode noise in high dv / dt signals is synchronized with the switching speed, and partial discharge signals are also mixed in, so the difference between the two cannot be significantly distinguished in either the time or frequency domain. Therefore, this method is not suitable for identifying square wave partial discharge signals with high dv / dt.

[0046] In related technologies, for ultra-wideband signals, partial discharge signals and interference waveforms can be acquired through synchronous triggering, and noise can be separated by combining signal calibration and interference suppression strategies. Signal calibration can be used to compensate for equipment or environmental losses. Interference suppression strategies can be used to reduce periodic interference estimated using the Fourier series method.

[0047] However, high-voltage power electronic devices are often used in inverters, where their small size, high integration, high voltage, and high frequency characteristics result in excellent performance. The aforementioned compensation methods cannot be used to compensate for square wave signals under any operating condition. Furthermore, the ultra-wideband signal in this technology is not an ultra-high frequency dv / dt signal; the compensation technique requires frequency consistency, making its application in high-frequency, high-dv / dt square waves extremely difficult.

[0048] Based on the above, this disclosure provides a testing method, apparatus, and electronic device for electronic devices, which can be applied to the testing process of electronic devices.

[0049] To facilitate understanding of this embodiment, a specific process of this disclosure embodiment is described below, such as... Figure 1 As shown in the embodiments of this disclosure, an embodiment of a testing method for an electronic device includes:

[0050] Step S101: Input the first detection signal into the initial system and acquire the first output signal generated by the initial system.

[0051] The initial system described above is typically a system without the device under test (DUT) connected. This system is usually a power system. The first detection signal is typically a square wave signal, but it can also be a combination of square wave signals and other signals; there are no restrictions on this. The first detection signal can be generated by a signal generator, etc.

[0052] After inputting the first detection signal into the initial system, it is necessary to obtain the first output signal generated by the initial system. Since there is no device under test in the initial system at this time, the first output signal can be regarded as a noise signal.

[0053] Step S102: Determine the first signal characteristics based on the first output signal.

[0054] When the first detection signal includes a square wave signal, the first output signal usually includes a pulse signal. These pulse signals can be regarded as noise signals generated by the initial system under the action of the first detection signal.

[0055] The aforementioned first signal feature can be calculated in various ways. It can be calculated based on one or more of the definitions of cross-entropy, KL divergence / relative entropy, JS divergence, and mutual information, to determine the first signal feature corresponding to the first output signal. These information features are typically used to evaluate the similarity between two events; in this method, they can be used to determine whether a signal is a noise signal or a partial discharge signal.

[0056] The aforementioned first signal feature is a characteristic of a noise signal, while the characteristics of a partial discharge signal need to be determined based on the definition of the corresponding information features. In subsequent processes, it is also necessary to determine whether the signal to be identified is a noise signal or a partial discharge signal based on the first signal feature and the characteristics of the partial discharge signal.

[0057] Step S103: Input the second detection signal into the target system and acquire the second output signal generated by the target system; the target system is formed by connecting the initial system and the device under test; the signal parameters of the second detection signal are consistent with those of the first detection signal.

[0058] The target system mentioned above refers to the system after the device under test (DUT) is connected to the initial system. The DUT can be a switch, cable, transformer, etc.

[0059] The second detection signal typically also includes a square wave signal. The square wave signal in the second detection signal has the same signal parameters as the square wave signal in the first detection signal. These signal parameters typically include amplitude, period, duty cycle, and frequency. The consistency of signal parameters between the second and first detection signals ensures that the noise signal generated by the circuitry in the initial system portion of the target system is similar to the first output signal. The second output signal typically includes noise signals and partial discharge signals caused by the device under test.

[0060] Step S104: Determine the morphological characteristics of the target signal based on the second output signal.

[0061] The aforementioned target signal morphology characteristics are typically used to describe the morphology of partial discharge signals generated by the device under test (DUT) in the target system. Partial discharge signals usually have specific morphologies, mainly depending on the discharge type and the phase coupling relationship between the power frequency electric field intensity. Common discharge types include floating discharge, tip discharge, surface discharge, and internal bubble discharge. Among them, floating discharge signals appear in both the positive and negative half-cycles of the power frequency phase, exhibiting a symmetrical distribution, large signal amplitude, high repeatability, and stable intervals between adjacent discharges. In the phase-resolved partial discharge spectrum (PRPD), it appears as a double-cluster pulse group, resembling a "double mushroom cloud." Tip discharge is concentrated near the peak of the negative half-cycle of the power frequency phase, presenting as a single-cluster pulse group. The signal intensity is weak but the frequency is high, and it appears as a single peak or double peak in the PRPD spectrum, with significant differences in the amplitude of the double peaks, etc.

[0062] Therefore, one or more obvious partial discharge signals can be identified from the second output signal, and then the morphological characteristics of the target signal can be determined based on these obvious partial discharge signals. The morphological characteristics of the target signal can typically include the pulse width, amplitude, and waveform asymmetry of the obvious partial discharge signals. A multidimensional vector can be generated based on these characteristics as the morphological features of the target signal.

[0063] Step S105: Based on the first signal characteristics and the target signal morphology characteristics, determine the partial discharge signal in the second output signal.

[0064] When the second detection signal includes a square wave signal, the second output signal generated by the target system after inputting the square wave signal typically includes noise and partial discharge signals. Both signals are usually displayed as pulse signals. In practical applications, it is necessary to determine the noise and partial discharge signals from the pulse signals of the second output signal based on the characteristics of the first signal and the morphological characteristics of the target signal.

[0065] When a square wave signal is input to the target system, the common-mode current generated by the rapid voltage changes during the generation of the rising and falling edges of the square wave signal will also appear as a pulse signal and can be considered as part of the noise signal. Therefore, it is quite difficult to identify the pulse signal output by the target system during the generation of the rising and falling edges of the square wave signal.

[0066] For the pulse signal output by the target system during the stable output of the square wave signal, it is possible to determine whether the pulse signal is a partial discharge signal or a noise signal based solely on whether the signal morphology of the pulse signal is similar to that of the target signal.

[0067] For the pulse signal output by the target system during the rising and falling edges of the square wave signal, we can first determine whether the signal morphology of the pulse signal is similar to that of the target signal. If they are similar, then based on the first signal characteristic and the pulse signal, we determine the values ​​of signal characteristics such as cross-entropy and relative entropy between them. Then, based on these values, we determine whether the pulse signal is similar to the first output signal (i.e., the "noise signal"), and thus determine whether the pulse signal is a partial discharge signal or a noise signal.

[0068] Step S106: Based on the first output signal and the partial discharge signal, determine the test result of the device under test.

[0069] The first output signal mentioned above includes a noise signal. After determining the noise signal and the partial discharge signal, their occurrence frequency and distribution trend can be determined respectively. Furthermore, their quantity and generation location can be compared to obtain the reliability test results for the device under test.

[0070] This method determines the partial discharge signal generated by the device under test through morphological and noise characteristics during the testing process of electronic devices, thereby improving the accuracy of partial discharge signal detection and thus improving the accuracy of the analysis results of the electronic device performance.

[0071] The following provides an embodiment for determining the characteristics of a first signal based on a first output signal.

[0072] In one embodiment, the first detection signal includes a first square wave signal, and the first output signal is generated by the initial system under the action of the first square wave signal. When the input detection signal is a square wave signal, the pulse signal in the output signal can be used as noise signal. The pulse signal in the first output signal can be identified first, specifically by filtering the pulse signal from the first output signal using a sliding window. Then, based on the pulse signal in the first output signal and the definition of relative entropy, the first signal characteristics are calculated.

[0073] Relative entropy, also known as Kullback-Leibler divergence (KL divergence for short), is an asymmetric measure of the difference between two probability distributions. Based on the definition of relative entropy, the probability distribution of pulse signals in the first output signal can be calculated as the first signal feature, which can then be used to determine whether the pulse signal to be identified is noise.

[0074] In one specific implementation, it is necessary to determine whether the signal quality in the second output signal is sufficient for the identification of partial discharge signals.

[0075] Typically, the second detection signal includes a second square wave signal, and the second output signal is generated by the target system under the action of the second square wave. Partial discharge signals may be insignificant at low voltages, making it difficult to differentiate them significantly from noise signals, resulting in a poor signal-to-noise ratio. After acquiring the second output signal, it can be first determined whether the second output signal includes a pulse signal with an amplitude greater than or equal to a specified amplitude. If it does, it indicates that the second output signal contains a local pulse signal with a high signal-to-noise ratio, allowing for subsequent partial discharge signal identification. If it does not, the voltage of the second square wave signal needs to be increased. Then, the second square wave signal with increased voltage is input to the target system, and the third output signal generated by the target system is acquired. The process continues to determine whether the third output signal includes a pulse signal with an amplitude greater than or equal to a specified amplitude. If it does, the second output signal is updated to the third output signal. If it does not, the voltage of the second square wave signal needs to be further increased, and the above operation is repeated until the output signal generated by the target system includes a pulse signal with an amplitude greater than or equal to the specified amplitude.

[0076] The following provides an example of determining the morphological characteristics of a target signal based on a second output signal.

[0077] In one approach, the second detection signal includes a second square wave signal; the second output signal is generated by the target system under the influence of the second square wave signal. The pulse signal in the second output signal can be identified first. In a specific implementation, the pulse signal can be identified from the second output signal using a sliding window method.

[0078] Then, the target pulse signal needs to be determined from the identified pulse signals. In specific implementation, the pulse signal generated during the voltage stabilization phase of the second square wave signal is identified from the identified pulse signals, and the target pulse signal is determined from the identified pulse signals. The pulse signal with the largest amplitude among the identified pulse signals can be determined as the target pulse signal. Alternatively, several pulse signals with large amplitudes can be morphologically fitted, and the fitted signal can then be determined as the target pulse signal.

[0079] After determining the target pulse signal, it is necessary to determine the target signal morphological characteristics based on the target pulse signal. Specifically, the target signal morphological characteristics can be generated based on information such as the pulse width, amplitude, and waveform asymmetry of the target pulse signal, so that the target signal morphological characteristics include this information.

[0080] The following provides an example of determining the partial discharge signal in the second output signal based on the characteristics of the first signal and the morphological characteristics of the target signal.

[0081] In one embodiment, the second detection signal includes a second square wave signal; the second output signal includes a target pulse signal generated by the initial system under the action of the second square wave signal. For each target pulse signal in the second output signal, the similarity between the signal morphological characteristics of the target pulse signal and the morphological characteristics of the target signal is first determined. The signal morphological characteristics of the target pulse signal also include information such as the pulse width, amplitude, and waveform asymmetry of the target pulse signal.

[0082] Then, based on the similarity, the first signal characteristics, and the voltage change state of the second square wave signal corresponding to the target pulse signal, it can be determined whether the target pulse signal is a partial discharge signal. In specific implementation, if the similarity is greater than or equal to a preset similarity threshold, it is determined whether the target pulse signal is at the rising or falling edge of the second square wave signal; if not, the target pulse signal is generated during a period of stable voltage and contains less noise, so the target pulse signal can be directly identified as a partial discharge signal. If it is, it is necessary to further determine whether the target pulse signal is a partial discharge signal based on the first signal characteristics.

[0083] As described above, the first signal characteristic is determined based on the definition of the first output signal and relative entropy. The relative entropy between the target pulse signal and the first output signal can be calculated based on the first signal characteristic. If the relative entropy result is greater than or equal to a preset threshold, the target pulse signal is determined to be a partial discharge signal. The relative entropy can be divided into two ranges: a value greater than or equal to 1 indicates a partial discharge signal, while a value less than 1 indicates a noise signal.

[0084] The following provides an example of determining the test results of the device under test based on the first output signal and the partial discharge signal.

[0085] In one embodiment, the first detection signal includes a first square wave signal; the first output signal includes a first pulse signal generated by the initial system under the action of the first square wave signal; the second detection signal includes a second square wave signal; and the second output signal includes a second pulse signal generated by the target system under the action of the second square wave signal. Based on the first pulse signal and the partial discharge signal, the Weibull distribution parameters of the partial discharge signal can be determined; and based on the Weibull distribution parameters, the test results of the device under test can be determined.

[0086] The aforementioned Weibull distribution parameters may include probability density distribution parameters, cumulative distribution parameters, or both. The probability density distribution parameters indicate the relationship between the intensity and frequency of the partial discharge signal and the first pulse signal; the cumulative distribution parameters indicate the distribution trend of the partial discharge signal and the first pulse signal.

[0087] The probability density distribution parameters can be calculated using the following Weibull probability density function (PDF) formula:

[0088] F(x; k, λ) = (k / λ) * (x / λ)^(k-1) * exp(-(x / λ)^k) (x ≥ 0) (1)

[0089] The cumulative distribution parameter can be calculated using the following formula for the Weibull cumulative distribution function:

[0090] F(x; k, λ) = 1 - exp(-(x / λ)^k) (x ≥ 0) (2)

[0091] Where k is the shape parameter, λ is the scale parameter, and x is a random variable, which in this paper is the pulse amplitude.

[0092] After calculating the Weibull distribution parameters, it can be determined whether the Weibull distribution parameters meet the preset parameter distribution range; if so, the test results are considered reliable. The Weibull distribution parameters include k and λ. For partial discharge signals, k is small and λ is large, while for noise, k is large and λ is small. Their ranges almost completely do not overlap. This can be understood as pulse signals whose k and λ are outside the parameter range of the partial discharge signal being considered noise. The parameter distribution range corresponding to the Weibull distribution parameters of the partial discharge signal is k[0.5, 1], λ[0.05, 1]. If the calculated Weibull distribution parameters meet this range, then the identified partial discharge signal and noise signal can be considered real, and therefore the test results are reliable.

[0093] The following provides a specific implementation method for testing a device under test using a square wave voltage signal.

[0094] like Figure 2 As shown, this process is implemented in the following specific way:

[0095] 1. Initialize the test process, prepare the copper-clad laminate to be tested, cover the copper-clad laminate with silicone gel, and build the test system.

[0096] In actual operating conditions, the ceramic copper-clad laminate (CCL) serves as the main internal circuitry of the power module, bearing high voltage. Silicone gel acts as internal insulation on each CCL, covering it. However, the electric field is often high at the points where the copper layer, ceramic layer, and the silicone gel come into contact with the CCL, making them prone to discharge. Therefore, the test sample of this invention is a CCL covered with silicone gel. The CCL is manufactured by a board manufacturer, and the silicone gel is obtained by mixing liquids A and B, which are then poured onto the bare CCL and solidify after a period of time, providing insulation and dust protection.

[0097] 2. Configure high-frequency sensors, such as photomultiplier tubes (PMTs) or high-frequency current sensors (HFCTs).

[0098] Specifically, a photomultiplier tube (PMT) is used for testing. Therefore, it is necessary to isolate the external natural light source and place the sample in a dark room, in which the PMT is also placed. According to the actual circuit, the different copper foils of the copper-clad laminate are connected to high voltage and ground. After a square wave is applied, the high-voltage copper foil and the grounded copper foil will continuously bear high-frequency square waves. These waveforms are displayed by an oscilloscope, thus forming a test system.

[0099] 3. Apply a square wave voltage to the system without a sample to obtain the first detection signal, which serves as the background noise sampling reference. For example... Figure 3 The image shows a 5.5V square wave voltage signal and the first detection signal generated under this square wave voltage signal (i.e., Figure 3 (detection signals in the middle); such as Figure 4 The image shows a 6.5V square wave voltage signal and the first detection signal generated under this square wave voltage signal (i.e., Figure 4 The detection signal contains many pulses with varying amplitudes, and it is impossible to distinguish which pulses are partial discharge signals or noise signals by human observation.

[0100] 4. Based on the pulse signal in the first detection signal, construct the information entropy feature and calculate the KL divergence of the noise.

[0101] 5. Apply a square wave voltage with the same parameters to the system containing the sample under test, and begin acquiring test data that may contain partial discharge signals, i.e., the second detection signal. For example... Figure 5 The image shows the second detection signal generated under a 5.5V square wave voltage signal, as shown below. Figure 6 The image shows the second detection signal generated under a 6.5V square wave voltage signal. Figure 5 and Figure 6 The results of identifying partial discharge signals and noise signals are also shown. Partial discharge signals and noise signals are labeled as triangles and circles, respectively.

[0102] 6. Determine if a pulse signal exists in the current waveform. If a clear pulse signal exists, perform pulse filtering using a sliding window. If no pulse appears, return to step 5 above and increase the voltage.

[0103] 7. Analyze the pulses identified by the sliding window and mark the position of the pulses in the square wave.

[0104] 8. Separate the pulse signals located at the rising and falling edges of the square wave in the second pulse signal from the pulse signals at other positions, and perform S4 KL divergence calculation on the pulses located at the rising and falling edges.

[0105] 9. Find the pulse with the largest amplitude among the pulses at stable voltage positions. Since the pulse at this position avoids dv / dt interference to some extent, the higher its amplitude, the stronger the discharge. Use this waveform as the standard partial discharge signal waveform, such as... Figure 7 As shown. A schematic diagram of the noise signal is shown below. Figure 8 As shown.

[0106] 10. Perform morphological feature statistics on the pulses at the remaining positions, and screen similar waveforms by combining information such as rise and fall time, asymmetry, amplitude, and pulse width, and select the remaining pulses that are similar to the pulse with the largest amplitude in S9.

[0107] Specifically, after finding the pulse that is not on the rising or falling edge and has the largest amplitude, the program records its pulse width, amplitude, waveform asymmetry and other information, and comprehensively constructs a P and Q comparison method similar to divergence information. The comprehensive characteristics of the largest waveform are taken as the benchmark and marked as 1. The closer the characteristics of the other waveforms are to it, the closer their ratio is to 1, and the closer they are to 0.

[0108] 11. Calculate the relative entropy KL divergence of the pulse obtained in step 10 above, and use it as the KL value of the partial discharge signal.

[0109] 12. Count the number of the two types of pulses obtained in steps 3 and 10 above, and use them as preliminary indicators of noise and partial discharge signal quantity.

[0110] 13. Probability density distribution diagram of the output partial discharge signal pulse (PDF), as shown. Figure 9 and Figure 10 As shown, this is used to observe the relationship between the intensity and frequency of partial discharge signals and noise during their occurrence.

[0111] 14. Output a partial discharge signal pulse cumulative distribution map (CDF) conforming to a Weibull distribution, such as... Figure 11 and Figure 12 As shown, this is used to observe the distribution trend of partial discharge signals and noise.

[0112] These two types of diagrams are for further verification of the judgments made before S11.

[0113] 15. Based on the obtained Weibull distribution parameters, compare the differences between the two types of pulses. If the parameters match the corresponding distribution range, the signal recognition is considered valid, and the number of the two types of pulses output by S12 is taken as the true number.

[0114] 16. End the entire testing process, complete data analysis and result output, and power off the testing system.

[0115] This method addresses the difficulty in identifying partial discharge signals from high-voltage, high-frequency, and high-dv / dt PWM square wave voltages. It combines statistical and morphological features to statistically analyze two types of signals. For noise: a square wave voltage with the above characteristics is applied to the sample without the sample being used. The pulse signal captured by the high-frequency sensor is used as a noise dataset, and a noise standard is established using relative entropy KL divergence. For partial discharge signals outside the rising and falling edges of the square wave: these pulses are less affected by dv / dt interference. The most typical discharge signal is obtained through a time sliding window, and similar pulses are sequentially searched based on morphological features. For partial discharge signals at the rising and falling edges of the square wave: these are most affected by high dv / dt, resulting in the most severe common-mode noise. The pulses often have high amplitudes and are the most difficult to distinguish. Here, information entropy KL divergence, morphological features, and Weibull distribution characteristics outside the rising and falling edges are statistically combined to determine whether it is a partial discharge signal, improving the accuracy of partial discharge signal identification and further enhancing the testing accuracy of electronic devices.

[0116] For the corresponding method embodiments described above, see [link to relevant documentation]. Figure 13 The diagram shows a structural schematic of a testing device for an electronic device, which includes:

[0117] The first signal acquisition module 1301 is used to input a first detection signal into the initial system and acquire the first output signal generated by the initial system;

[0118] The first signal feature determination module 1302 is used to determine the first signal features based on the first output signal;

[0119] The second signal acquisition module 1303 is used to input a second detection signal to the target system and acquire a second output signal generated by the target system; the target system is formed by connecting the initial system and the device under test; the signal parameters of the second detection signal are the same as those of the first detection signal;

[0120] The signal morphology feature determination module 1304 is used to determine the morphology features of the target signal based on the second output signal;

[0121] The partial discharge signal determination module 1305 is used to determine the partial discharge signal in the second output signal based on the first signal characteristics and the target signal morphological characteristics.

[0122] The test result determination module 1306 is used to determine the test result of the device under test based on the first output signal and the partial discharge signal.

[0123] The aforementioned testing apparatus for electronic devices inputs a first detection signal to an initial system and acquires a first output signal generated by the initial system; determines a first signal characteristic based on the first output signal; inputs a second detection signal to a target system and acquires a second output signal generated by the target system; the target system is formed by connecting the initial system and the device under test; the signal parameters of the second detection signal are consistent with those of the first detection signal; determines the target signal morphological characteristics based on the second output signal; determines the partial discharge signal in the second output signal based on the first signal characteristic and the target signal morphological characteristics; and determines the test result of the device under test based on the first output signal and the partial discharge signal.

[0124] This method determines the partial discharge signal generated by the device under test through morphological and noise characteristics during the testing process of electronic devices, thereby improving the accuracy of partial discharge signal detection and thus improving the accuracy of the analysis results of the electronic device performance.

[0125] The first detection signal mentioned above includes a first square wave signal; the first output signal is generated by the initial system under the action of the first square wave signal; the first signal feature determination module is also used to: calculate the first signal feature based on the definition of the pulse signal and relative entropy in the first output signal.

[0126] The aforementioned second detection signal includes a second square wave signal; the second output signal is generated by the target system under the action of the second square wave; the aforementioned device further includes: a first amplitude judgment module, used to determine whether the second output signal includes a pulse signal with an amplitude greater than or equal to a specified amplitude; a voltage boosting module, used to increase the voltage of the second square wave signal if it does not include a pulse signal; a third signal acquisition module, used to input the voltage-boosted second square wave signal to the target system and acquire the third output signal generated by the target system; a second amplitude judgment module, used to determine whether the third output signal includes a pulse signal with an amplitude greater than or equal to a specified amplitude; and a signal update module, used to update the second output signal to the third output signal if it does include a pulse signal.

[0127] The second detection signal mentioned above includes a second square wave signal; the second output signal is generated by the target system under the action of the second square wave signal; the signal morphology feature determination module is also used to: identify the pulse signal in the second output signal; determine the target pulse signal from the identified pulse signal; and determine the target signal morphology feature based on the target pulse signal.

[0128] The aforementioned signal morphology feature determination module is also used to: determine the pulse signal generated during the voltage stabilization phase of the second square wave signal from the identified pulse signals; and determine the target pulse signal from the determined pulse signals.

[0129] The aforementioned signal morphology feature determination module is also used to: determine the pulse signal with the largest amplitude among the determined pulse signals as the target pulse signal.

[0130] The aforementioned target signal morphological characteristics include at least the following information: the pulse width, amplitude, and waveform asymmetry of the target pulse signal.

[0131] The second detection signal mentioned above includes a second square wave signal; the second output signal includes a target pulse signal generated by the initial system under the action of the second square wave signal; the partial discharge signal determination module is further used to: determine the similarity between the signal morphology features of the target pulse signal and the target signal morphology features for each target pulse signal in the second output signal; and determine whether the target pulse signal is a partial discharge signal based on the similarity, the first signal features and the voltage change state of the second square wave signal corresponding to the target pulse signal.

[0132] The aforementioned partial discharge signal determination module is further configured to: if the similarity is greater than or equal to a preset similarity threshold, determine whether the target pulse signal is at the rising or falling edge of the second square wave signal; if not, determine the target pulse signal as a partial discharge signal; if so, determine whether the target pulse signal is a partial discharge signal based on the first signal characteristics.

[0133] The aforementioned first signal feature is determined based on the definition of the first output signal and relative entropy; the partial discharge signal determination module is also used to: calculate the relative entropy result between the target pulse signal and the first output signal based on the first signal feature; if the relative entropy result is greater than or equal to a preset threshold, determine that the target pulse signal is a partial discharge signal.

[0134] The first detection signal includes a first square wave signal; the first output signal includes a first pulse signal generated by the initial system under the action of the first square wave signal; the second detection signal includes a second square wave signal; the second output signal includes a second pulse signal generated by the target system under the action of the second square wave signal; the test result determination module is further used to: determine the Weibull distribution parameters of the partial discharge signal based on the first pulse signal and the partial discharge signal; and determine the test result of the device under test based on the Weibull distribution parameters.

[0135] The aforementioned Weibull distribution parameters include probability density distribution parameters and cumulative distribution parameters; the probability density distribution parameters are used to indicate the correspondence between the intensity and frequency of the partial discharge signal and the first pulse signal when they are generated; the cumulative distribution parameters are used to indicate the distribution trend of the partial discharge signal and the first pulse signal.

[0136] The aforementioned device further includes: a parameter distribution judgment module, used to determine whether the Weibull distribution parameters meet the preset parameter distribution range; if they do, the test results are determined to be reliable.

[0137] This embodiment also provides an electronic device, including a processor and a memory. The memory stores machine-executable instructions that can be executed by the processor, and the processor executes the machine-executable instructions to implement the above-mentioned testing method for the electronic device.

[0138] See Figure 14 As shown, the electronic device includes a processor 100 and a memory 101. The memory 101 stores machine-executable instructions that can be executed by the processor 100. The processor 100 executes the machine-executable instructions to implement the testing method of the electronic device.

[0139] Furthermore, Figure 14 The electronic device shown also includes a bus 102 and a communication interface 103, with the processor 100, the communication interface 103 and the memory 101 connected via the bus 102.

[0140] The memory 101 may include high-speed random access memory (RAM) and may also include non-volatile memory, such as at least one disk storage device. Communication between this system network element and at least one other network element is achieved through at least one communication interface 103 (which can be wired or wireless), such as the Internet, wide area network, local area network, metropolitan area network, etc. The bus 102 may be an ISA bus, PCI bus, or EISA bus, etc. The bus can be divided into address bus, data bus, control bus, etc. For ease of representation, Figure 14 The symbol is represented by a single double-headed arrow, but this does not mean that there is only one bus or one type of bus.

[0141] Processor 100 may be an integrated circuit chip with signal processing capabilities. In implementation, each step of the above method can be completed by the integrated logic circuitry in the hardware of processor 100 or by instructions in software form. Processor 100 may be a general-purpose processor, including a Central Processing Unit (CPU), a Network Processor (NP), etc.; it may also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field-Programmable Gate Array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. It can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of this invention. The general-purpose processor may be a microprocessor or any conventional processor. The steps of the methods disclosed in the embodiments of this invention can be directly manifested as execution by a hardware decoding processor, or execution by a combination of hardware and software modules in the decoding processor. The software module can reside in a readily available storage medium in the art, such as random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, or registers. This storage medium is located in memory 101, and the processor 100 reads the information from memory 101 and, in conjunction with its hardware, completes the steps of the method described in the foregoing embodiments.

[0142] This embodiment also provides a machine-readable storage medium storing machine-executable instructions. When the machine-executable instructions are called and executed by a processor, the machine-executable instructions cause the processor to implement the test method for the above-mentioned electronic device.

[0143] The present invention provides a testing method, apparatus, and electronic device for electronic devices, including a computer-readable storage medium storing program code, wherein the instructions included in the program code can be used to execute the methods described in the preceding method embodiments.

[0144] See Figure 14 As shown, the electronic device includes a processor 100 and a memory 101. The memory 101 stores machine-executable instructions that can be executed by the processor 100. The processor 100 executes the machine-executable instructions to implement the testing method of the electronic device.

[0145] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working process of the system and apparatus described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0146] Furthermore, in the description of the embodiments of this disclosure, unless otherwise expressly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this disclosure based on the specific circumstances.

[0147] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this disclosure, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this disclosure. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0148] In the description of this disclosure, it should be noted that the terms "center," "upper," "lower," "left," "right," "vertical," "horizontal," "inner," and "outer," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings, and are only for the convenience of describing this disclosure and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of this disclosure. Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0149] Finally, it should be noted that the above embodiments are merely specific implementations of this disclosure, used to illustrate the technical solutions of this disclosure, and not to limit it. The protection scope of this disclosure is not limited thereto. Although this disclosure has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that any person skilled in the art can still modify or easily conceive of changes to the technical solutions described in the foregoing embodiments, or make equivalent substitutions for some of the technical features, within the scope of the technology disclosed in this disclosure. Such modifications, changes, or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this disclosure, and should all be covered within the protection scope of this disclosure. Therefore, the protection scope of this disclosure should be determined by the protection scope of the claims.

Claims

1. A testing method for electronic devices, characterized in that, The method includes: Input a first detection signal into the initial system and acquire the first output signal generated by the initial system; Based on the first output signal, determine the first signal characteristics; A second detection signal is input to the target system, and a second output signal generated by the target system is acquired; the target system is formed by connecting the initial system and the device under test; the signal parameters of the second detection signal are consistent with those of the first detection signal. Based on the second output signal, the morphological characteristics of the target signal are determined; Based on the first signal characteristics and the target signal morphological characteristics, the partial discharge signal in the second output signal is determined; Based on the first output signal and the partial discharge signal, the test result of the device under test is determined.

2. The method according to claim 1, characterized in that, The first detection signal includes a first square wave signal; the first output signal is generated by the initial system under the action of the first square wave signal; The step of determining the first signal feature based on the first output signal includes: Based on the definition of pulse signal and relative entropy in the first output signal, the characteristics of the first signal are calculated.

3. The method according to claim 1, characterized in that, The second detection signal includes a second square wave signal; the second output signal is generated by the target system under the action of the second square wave. Before determining the target signal morphological features based on the second output signal, the method further includes: Determine whether the second output signal includes a pulse signal with an amplitude greater than or equal to a specified amplitude; If not, increase the voltage of the second square wave signal; A second square wave signal with increased voltage is input to the target system, and a third output signal generated by the target system is acquired. Determine whether the third output signal includes a pulse signal with an amplitude greater than or equal to a specified amplitude; If included, the second output signal is updated to the third output signal.

4. The method according to claim 1, characterized in that, The second detection signal includes a second square wave signal; the second output signal is generated by the target system under the action of the second square wave signal; The step of determining the morphological features of the target signal based on the second output signal includes: Identify the pulse signal in the second output signal; Determine the target pulse signal from the identified pulse signals; Based on the target pulse signal, the morphological characteristics of the target signal are determined.

5. The method according to claim 4, characterized in that, The steps for determining the target pulse signal from the identified pulse signals include: From the identified pulse signals, determine the pulse signals generated during the voltage stabilization phase of the second square wave signal; The target pulse signal is determined from the identified pulse signals.

6. The method according to claim 5, characterized in that, The steps for determining the target pulse signal from the identified pulse signals include: The pulse signal with the largest amplitude among the identified pulse signals is determined as the target pulse signal.

7. The method according to claim 4, characterized in that, The morphological characteristics of the target signal include at least the following information: the pulse width, amplitude, and waveform asymmetry of the target pulse signal.

8. The method according to claim 1, characterized in that, The second detection signal includes a second square wave signal; the second output signal includes a target pulse signal generated by the initial system under the action of the second square wave signal. The step of determining the partial discharge signal in the second output signal based on the first signal characteristics and the target signal morphological characteristics includes: For each target pulse signal in the second output signal, determine the similarity between the signal morphological features of the target pulse signal and the morphological features of the target signal; Based on the similarity, the first signal characteristics, and the voltage change state of the second square wave signal corresponding to the target pulse signal, it is determined whether the target pulse signal is a partial discharge signal.

9. The method according to claim 8, characterized in that, The step of determining whether the target pulse signal is a partial discharge signal based on the similarity, the first signal features, and the voltage change state of the second square wave signal corresponding to the target pulse signal includes: If the similarity is greater than or equal to a preset similarity threshold, determine whether the target pulse signal is at the rising or falling edge of the second square wave signal; If not, the target pulse signal is determined to be a partial discharge signal; If so, based on the first signal characteristic, determine whether the target pulse signal is a partial discharge signal.

10. The method according to claim 8, characterized in that, The first signal feature is determined based on the definition of the first output signal and relative entropy; The step of determining whether the target pulse signal is a partial discharge signal based on the first signal feature includes: Based on the first signal characteristics, the relative entropy between the target pulse signal and the first output signal is calculated; If the relative entropy result is greater than or equal to a preset threshold, the target pulse signal is determined to be a partial discharge signal.

11. The method according to claim 1, characterized in that, The first detection signal includes a first square wave signal; the first output signal includes a first pulse signal generated by the initial system under the action of the first square wave signal. The second detection signal includes a second square wave signal; the second output signal includes a second pulse signal generated by the target system under the action of the second square wave signal; The step of determining the test result of the device under test based on the first output signal and the partial discharge signal includes: Based on the first pulse signal and the partial discharge signal, determine the Weibull distribution parameters of the partial discharge signal; The test results of the device under test are determined based on the Weibull distribution parameters.

12. The method according to claim 11, characterized in that, The Weibull distribution parameters include probability density distribution parameters and cumulative distribution parameters; The probability density distribution parameter is used to indicate the correspondence between the intensity and frequency of the partial discharge signal and the first pulse signal when they are generated. The cumulative distribution parameter is used to indicate the distribution trend of the partial discharge signal and the first pulse signal.

13. The method according to claim 11, characterized in that, The method further includes: Determine whether the Weibull distribution parameters meet the preset parameter distribution range; If the conditions are met, the test results are deemed reliable.

14. A testing apparatus for electronic devices, characterized in that, The device includes: The first signal acquisition module is used to input a first detection signal into the initial system and acquire the first output signal generated by the initial system; The first signal feature determination module is used to determine a first signal feature based on the first output signal; The second signal acquisition module is used to input a second detection signal to the target system and acquire a second output signal generated by the target system; the target system is formed by connecting the initial system and the device under test; the signal parameters of the second detection signal are the same as those of the first detection signal. The signal morphology feature determination module is used to determine the morphology features of the target signal based on the second output signal; A partial discharge signal determination module is used to determine the partial discharge signal in the second output signal based on the first signal characteristics and the target signal morphological characteristics; The test result determination module is used to determine the test result of the device under test based on the first output signal and the partial discharge signal.

15. An electronic device, characterized in that, It includes a processor and a memory, the memory storing machine-executable instructions that can be executed by the processor, the processor executing the machine-executable instructions to implement the test method of the electronic device according to any one of claims 1-13.

16. A machine-readable storage medium, characterized in that, The machine-readable storage medium stores machine-executable instructions, which, when invoked and executed by a processor, cause the processor to implement the test method for the electronic device according to any one of claims 1-13.

Images