A method, system, device and storage medium for automatically identifying the starting point of a partial discharge pulse signal

Abstract

The present invention discloses a method, system, device and storage medium for automatically identifying the starting point of a partial discharge pulse signal, and relates to the field of signal processing technology. The method comprises: acquiring a partial discharge high-frequency electromagnetic wave signal and calculating a corresponding cumulative energy curve; determining the initial pulse starting moment based on the cumulative energy curve, setting two time windows based on the initial pulse starting moment, and calculating a corresponding reference time point; calculating a first slope and a second slope based on the initial pulse starting moment and the reference time point, and performing a comparative judgment; outputting the final signal starting moment based on the result of the comparative judgment; the present invention effectively reduces the misjudgment rate and recognition time, avoids the influence of interference signals and algorithm anomalies, provides stable and accurate starting point identification for partial discharge monitoring, helps to timely discover hidden faults of electrical equipment, and ensures the safe operation of the equipment.

Description

Technical Field

[0001] The present invention relates to the field of signal processing technology, and in particular to a method, system, device and storage medium for automatically identifying the starting point of a partial discharge pulse signal. Background Art

[0002] Partial discharge detection is a crucial tool for GIS / GIL insulation condition monitoring and fault early warning. Defect location is a crucial component of defect detection and diagnosis. High-precision positioning is the foundation for accurate fault diagnosis. Defect location not only helps determine defect severity but also facilitates subsequent troubleshooting and defect elimination.

[0003] Currently, the commonly used methods for partial discharge detection on-site are ultra-high frequency (UHF) and ultrasonic methods, both of which can be used for defect location. Both UHF and ultrasonic detection methods use signal arrival time differences (TDAs) for positioning. When partial discharge occurs in a GIS / GIL defect, electromagnetic and ultrasonic signals are generated. UHF or ultrasonic sensors are deployed at different locations on the GIS / GIL equipment to detect the discharge signal from the same source. The position of the source relative to the sensors is then calculated based on the arrival time differences of the signals received by each sensor and the propagation speed of the electromagnetic or ultrasonic waves within the GIS / GIL. Determining the TDAs between the sensor signals is the basis for location determination. Currently, the TDAs between the starting points of the partial discharge pulse signals are commonly used to determine the TDAs between the sensor signals. Inaccurate signal starting points lead to inaccurate TDAs. Given the high propagation speed of UHF signals, even small TDAs calculation errors can result in large TDAs. For example, if the TDAs calculation error is 10 ns, the TDAs positioning error based on the UHF signal TDAs is 3 meters. However, within GIS / GIL, there may be multiple insulating parts within a 3m range. Such positioning accuracy makes it impossible to accurately determine the location of defects, which brings difficulties to subsequent operation, maintenance and defect control. Summary of the Invention

[0004] In view of the above-mentioned problems, the present invention is proposed.

[0005] Therefore, the technical problem solved by the present invention is: how to efficiently and accurately identify the starting point of the GIS / GIL partial discharge pulse signal, so as to solve the problem of large errors in the existing method when processing signals with slow wave heads, and meet the demand for high-precision defect positioning.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0007] In a first aspect, an embodiment of the present invention provides a method for automatically identifying a starting point of a partial discharge pulse signal, comprising:

[0008] As a preferred solution for the automatic identification method of the starting point of a partial discharge pulse signal, wherein:

[0009] The obtaining of the partial discharge high-frequency electromagnetic wave signal and calculating the corresponding cumulative energy curve includes:

[0010] The local discharge high-frequency electromagnetic wave signal of a specific format and length is read, and the sampling time interval is determined according to the system sampling rate. For the electromagnetic wave signal, the corresponding cumulative energy curve is calculated in a discrete form, and the relevant parameters of the discrete form correspond to the time length of the signal and the sampling time interval.

[0011] As a preferred solution for the automatic identification method of the starting point of a partial discharge pulse signal, wherein:

[0012] Determining the initial pulse starting time based on the cumulative energy curve includes:

[0013] The global minimum point of the energy accumulation curve is obtained, and the time coordinate of the minimum point is used as the starting time of the initial pulse of the electromagnetic wave signal.

[0014] The beneficial effects of this preferred technical solution are: using the global minimum point of the energy accumulation curve to determine the starting time of the initial pulse. The method is simple and intuitive, and can quickly locate the possible starting time of the electromagnetic wave signal, providing an initial reference for subsequent accurate identification and reducing the blindness of subsequent calculations.

[0015] As a preferred solution for the automatic identification method of the starting point of a partial discharge pulse signal, wherein:

[0016] Calculating the first slope and the second slope includes:

[0017] The first slope represents the average rate of change between the reference time point corresponding to the first time window and the reference time point corresponding to the second time window on the cumulative energy curve.

[0018] The beneficial effect of this preferred technical solution is that by calculating the first slope between reference points in a specific time window on the cumulative energy curve, the change of the cumulative energy curve in the interval can be quantified, which provides an important characteristic indicator for the subsequent judgment of the starting point of the signal, and helps to more accurately analyze the change trend of the signal.

[0019] As a preferred solution for the automatic identification method of the starting point of a partial discharge pulse signal, wherein:

[0020] Calculating the first slope and the second slope further includes:

[0021] The second slope represents the average rate of change between the reference time point corresponding to the first time window and the initial pulse starting point on the cumulative energy curve.

[0022] The beneficial effects of this preferred technical solution are: calculating the second slope, combining it with the first slope, and performing a comprehensive analysis of the changes in the cumulative energy curve in different intervals, which can more comprehensively grasp the changing characteristics of the signal at different stages and further improve the accuracy of identifying the starting point of the partial discharge pulse signal.

[0023] As a preferred solution for the automatic identification method of the starting point of a partial discharge pulse signal, wherein:

[0024] The outputting of the final signal starting point time according to the comparison and judgment result includes:

[0025] If the relative difference between the first slope and the second slope is within the preset percentage, the calculation is terminated and the output of the final signal starting time is t s ; Otherwise, perform iterative calculation.

[0026] The advantageous effects of this preferred technical solution are: by comparing the relative difference between the first slope and the second slope and combining it with a preset percentage, the final signal starting point can be promptly determined when certain conditions are met, thereby improving recognition efficiency. Furthermore, iterative calculations are performed for cases where the conditions are not met, ensuring the accuracy of the recognition results.

[0027] As a preferred solution for the automatic identification method of the starting point of a partial discharge pulse signal, wherein:

[0028] The iterative calculation includes:

[0029] Move the signal starting time forward by one sampling point. If the signal starting time is 0, end the calculation and output the final signal starting time as 0.

[0030] Otherwise, the second slope is recalculated and the first slope and the second slope are compared and judged until the starting point of the final signal is output.

[0031] The beneficial effects of this preferred technical solution are: the iterative calculation process, by gradually advancing the signal starting point and recalculating the slope for comparison and judgment, can continuously approach the true signal starting point, thereby improving recognition accuracy. Furthermore, setting the condition of terminating the calculation when the signal starting point is 0 avoids infinite iterations and ensures the stability and reliability of the algorithm.

[0032] In a second aspect, an embodiment of the present invention provides a system for automatically identifying the starting point of a partial discharge pulse signal, comprising:

[0033] The cumulative energy curve generation module is used to obtain the high-frequency electromagnetic wave signal of partial discharge and calculate the corresponding cumulative energy curve;

[0034] A reference time point calculation module is used to determine the initial pulse starting time based on the cumulative energy curve, set two time windows based on the initial pulse starting time, and calculate the corresponding reference time point;

[0035] The starting point identification module is used to calculate the first slope and the second slope based on the initial pulse starting time and the reference time point, and compare and judge; according to the result of the comparison and judgment, the final signal starting time is output.

[0036] In a third aspect, an embodiment of the present invention provides an electronic device, including:

[0037] memory and processor;

[0038] The memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions. When the one or more programs are executed by the one or more processors, the one or more processors implement the method for automatically identifying the starting point of a partial discharge pulse signal as described in any embodiment of the present invention.

[0039] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the method for automatically identifying the starting point of a partial discharge pulse signal.

[0040] Beneficial effects of the present invention: After obtaining the local discharge high-frequency electromagnetic wave signal, the present invention determines the sampling time interval based on the system sampling rate, and calculates the cumulative energy curve in discrete form, and the discrete parameters correspond to the signal time length and the sampling time interval. This method closely fits the actual signal processing scenario and more accurately reflects the accumulation of signal energy; by finding the global minimum point of the energy accumulation curve to determine the starting moment of the initial pulse, the operation is simple and the calculation speed is fast, and the possible starting moment of the electromagnetic wave signal can be located in a short time; by calculating the first slope and the second slope of different intervals on the cumulative energy curve, the average rate of change between the reference points of the specific time window and between the first time window reference point and the starting moment of the initial pulse is quantified, respectively, so that the changing characteristics of the signal can be grasped more comprehensively and meticulously; a comprehensive analysis is performed in combination with the first slope and the second slope, which provides a richer and more accurate basis for judging the starting point of the local discharge pulse signal, and can more effectively eliminate the influence of interference signals and improve Reliability of starting point identification; based on the relative difference between the first slope and the second slope and the preset percentage, the judgment is made, and when the difference is within the preset range, the final signal starting point moment is determined in time, avoiding unnecessary calculations; iterative calculations are performed for situations where the conditions are not met, while ensuring the accuracy of recognition, the recognition efficiency is significantly improved; during the iterative calculation process, by gradually moving the signal starting point moment forward and recalculating the slope for comparison and judgment, the true signal starting point can be continuously approached, thereby improving the recognition accuracy; the present invention effectively reduces the misjudgment rate and recognition time, avoids the influence of interference signals and algorithm anomalies, provides stable and accurate starting point identification for partial discharge monitoring, helps to timely discover hidden dangers of electrical equipment failures, and ensures the safe operation of equipment. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0042] Figure 1 This is an overall flow chart of the method for automatically identifying the starting point of a partial discharge pulse signal provided by the present invention;

[0043] Figure 2 It is the starting point identification result of the traditional method for the pulse signal with a steep wave head in the simulation example of the automatic identification method of the starting point of the partial discharge pulse signal provided by the present invention;

[0044] Figure 3 It is the starting point identification result of the traditional method for the pulse signal with a relatively slow wave head in the simulation example of the automatic identification method of the starting point of the partial discharge pulse signal provided by the present invention;

[0045] Figure 4 It is the result of identifying the starting point of a pulse signal based on the minimum value of the cumulative energy defect in the simulation example of the method for automatically identifying the starting point of a partial discharge pulse signal provided by the present invention;

[0046] Figure 5 It is the result of identifying the starting point of a pulse signal based on the change in the slope of the cumulative energy curve in the simulation example of the method for automatically identifying the starting point of a partial discharge pulse signal provided by the present invention. DETAILED DESCRIPTION

[0047] To make the above-mentioned objects, features, and advantages of the present invention more clearly understood, the following detailed description of the specific embodiments of the present invention is given in conjunction with the accompanying drawings. It is obvious that the described embodiments are only part of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in this field without creative work should fall within the scope of protection of the present invention.

[0048] Example 1, reference Figure 1 , which is the first embodiment of the present invention, provides a method for automatically identifying the starting point of a partial discharge pulse signal, comprising:

[0049] S1: Obtain the high-frequency electromagnetic wave signal of partial discharge and calculate the corresponding cumulative energy curve;

[0050] S2: Based on the cumulative energy curve, determine the initial pulse starting time, set two time windows based on the initial pulse starting time, and calculate the corresponding reference time points;

[0051] S3: Based on the initial pulse starting time and the reference time point, calculate the first slope and the second slope and compare and judge; output the final signal starting time according to the result of the comparison and judgment.

[0052] It should be noted that, through steps S1-S3, this embodiment first obtains the local discharge high-frequency electromagnetic wave signal and calculates the cumulative energy curve, then determines the initial pulse starting time based on the curve, sets the time window and calculates the reference time point, and finally calculates the first slope and the second slope for comparison and judgment to output the final signal starting time. This can effectively overcome the large error problem existing in the traditional method when processing the starting point identification of the local discharge pulse signal, especially for signals with a slower wave head, and can more accurately identify the starting point, providing reliable technical support for the batch identification, analysis and defect location of local discharge signals of defects in GIS / GIL, helping to achieve more accurate automatic defect location, and improving the efficiency and accuracy of power system operation and maintenance and defect control.

[0053] Example 2, reference Figure 1, which is an embodiment of the present invention, provides a method for automatically identifying the starting point of a partial discharge pulse signal based on the previous embodiment, comprising:

[0054] In this embodiment, the step S1 of acquiring the partial discharge high-frequency electromagnetic wave signal and calculating the corresponding cumulative energy curve includes:

[0055] Exemplarily, the partial discharge high-frequency electromagnetic wave signal u(t) is read, the data format is csv format, the data length is 2000, the system sampling rate is 5Gsps, and the sampling time interval Δt is obtained, which is 0.2ns.

[0056] Calculate the cumulative energy curve S(t) of the electromagnetic wave signal u(t);

[0057] Specifically, for a signal u(t) with a time length of T, its cumulative energy curve The calculation method is the continuous integration form:

[0058] ,

[0059] In actual calculation, the discrete form is adopted, which is expressed as:

[0060] ,

[0061] Where S(k) is the discrete form of S(t), u(n) is the discrete form of u(t), N is the length of the discrete form of u(n), and N=T / △t.

[0062] It should be noted that the calculation of the cumulative energy curve provides a basis for the subsequent determination of the signal starting point.

[0063] In another possible implementation, when calculating the cumulative energy curve, a weighting factor may be introduced based on the original cumulative energy curve.

[0064] For example, weights can be set based on the frequency characteristics of the signal, with lower weights assigned to high-frequency components because they are severely attenuated after long-distance propagation. Assuming the frequency distribution of the signal can be obtained using a fast Fourier transform (FFT), weights of 0.5 are assigned to components with frequencies above a certain threshold, and 1 to components with frequencies below the threshold.

[0065] The cumulative energy curve can also be processed by moving average to smooth the curve and reduce the impact of noise.

[0066] In this embodiment, determining the initial pulse starting time based on the cumulative energy curve in step S2 includes:

[0067] The ergodic method is used to find the global minimum point of the energy accumulation curve (tmin ,S(t min )), determine the initial pulse starting time t of the electromagnetic wave signal s =t min .

[0068] In this embodiment, in step S2, two time windows are set based on the initial pulse starting time, and the calculation of the corresponding reference time points includes:

[0069] Two time windows are set based on the starting time of the initial pulse, and in this embodiment, the 1 / 10 window and the 1 / 2 window are preferably used;

[0070] Calculate the corresponding reference time point, expressed as:

[0071] t1=[(t min / △t ) / 10]×△t

[0072] t2=[(t min / △t ) / 2] ×△t

[0073] Wherein, t1 is the reference time point corresponding to the first time window, and t2 is the reference time point corresponding to the second time window.

[0074] It should be noted that according to the physical meaning of the cumulative energy curve, before the pulse start time of the electromagnetic wave signal, that is, t min Previously, S(t) decreased approximately linearly. The calculation of t1 and t2 was to select two points on the linear decrease interval of S(t) for subsequent slope calculation.

[0075] In this embodiment, in step S3, the first slope and the second slope are calculated based on the initial pulse starting time and the reference time point, and compared and judged; outputting the final signal starting time according to the result of the comparison and judgment includes:

[0076] First slope Expressed as:

[0077] ,

[0078] Second slope Expressed as:

[0079] ,

[0080] In another possible implementation, the first slope can be calculated by using three points on the cumulative energy curve and fitting a straight line y=ax+b using the least squares method, where a is the first slope. , , The second slope is calculated using a similar method by selecting three more points.

[0081] In another possible implementation, the window size for slope calculation can be adaptively adjusted based on signal characteristics. For signals with steeper peaks, the window size can be smaller; for signals with gentler peaks, the window size can be larger. For example, the signal's steepness can be determined by calculating its variance. When the variance is greater than a certain threshold, the window size is set to W1; when the variance is less than the threshold, the window size is set to W2 (W2 > W1). The slope is then calculated within the corresponding window.

[0082] Comparing and judging the first slope and the second slope;

[0083] Specifically, the step of comparing and judging the first slope and the second slope includes:

[0084] like , then the calculation ends and the output of the final signal starting time is t s ; Otherwise, perform iterative calculation.

[0085] Specifically, the iterative calculation steps include:

[0086] Let t s =t s -△t, if t s =0, the calculation ends and the output of the final signal starts at time t s ;

[0087] Otherwise, the second slope is recalculated and the first slope and the second slope are compared and judged until the starting point of the final signal is output.

[0088] It should be noted that before the signal starting point, the cumulative energy curve is approximately a straight line decline, and after the starting point, the slope of the cumulative energy curve changes. Therefore, the signal starting point can be determined by judging the slope error at different points on the cumulative energy curve.

[0089] Example 3. The above is a schematic diagram of the method for automatically identifying the starting point of a partial discharge pulse signal according to this embodiment. It should be noted that the technical solution of the automatic identification system for the starting point of a partial discharge pulse signal and the technical solution of the automatic identification method for the starting point of a partial discharge pulse signal are based on the same concept. For details not described in detail in the technical solution of the automatic identification system for the starting point of a partial discharge pulse signal in this embodiment, please refer to the description of the technical solution of the automatic identification method for the starting point of a partial discharge pulse signal.

[0090] This embodiment further provides a system for automatically identifying the starting point of a partial discharge pulse signal, comprising:

[0091] The cumulative energy curve generation module is used to obtain the high-frequency electromagnetic wave signal of partial discharge and calculate the corresponding cumulative energy curve;

[0092] A reference time point calculation module is used to determine the initial pulse starting time based on the cumulative energy curve, set two time windows based on the initial pulse starting time, and calculate the corresponding reference time point;

[0093] The starting point identification module is used to calculate the first slope and the second slope based on the initial pulse starting time and the reference time point, and compare and judge; according to the result of the comparison and judgment, the final signal starting time is output.

[0094] This embodiment further provides an electronic device applicable to the method for automatically identifying the starting point of a partial discharge pulse signal, comprising:

[0095] Memory and processor; the memory is used to store computer executable instructions, and the processor is used to execute computer executable instructions to implement the method for automatically identifying the starting point of a partial discharge pulse signal as proposed in the above embodiment.

[0096] This embodiment further provides a storage medium storing a computer program. When the program is executed by a processor, the method for automatically identifying the starting point of a partial discharge pulse signal as proposed in the above embodiment is implemented.

[0097] The storage medium proposed in this embodiment and the method for automatically identifying the starting point of a partial discharge pulse signal proposed in the above embodiment belong to the same inventive concept. For technical details not fully described in this embodiment, please refer to the above embodiment, and this embodiment has the same beneficial effects as the above embodiment.

[0098] Example 4, reference Figure 2-Figure 5 , which is an embodiment of the present invention, provides a method for automatically identifying the starting point of a partial discharge pulse signal. In order to verify the beneficial effects of the present invention, scientific demonstration is carried out through simulation experiments.

[0099] Drawing based on actual test data Figure 2-Figure 5 ,The acquisition conditions in the figure are sampling rate 5GS / s and sampling interval 0.2ns; Figure 2 and Figure 3 The signal length is 1000, Figure 4 and Figure 5 The acquisition length is 2000, the blue is the original electromagnetic wave signal, and the red is the cumulative energy curve.

[0100] It should be noted that commonly used methods for obtaining the starting point of a pulse signal include the threshold method and the energy difference method. Among them, the principle of the threshold method is simple, that is, when the signal amplitude reaches a preset threshold for the first time, that point is regarded as the pulse starting point. The advantage of this method is that it is simple and intuitive and does not require complex calculations, but the size of its error depends on the choice of the threshold. The principle of the energy accumulation method is that since the signal energy is proportional to the square of the signal amplitude, the signal amplitude can be used to draw a cumulative energy curve, and the time corresponding to the minimum point of the cumulative energy curve is regarded as the starting point of the pulse signal. This method does not require setting any parameters and is easy to implement automatic calculation.

[0101] The traditional cumulative energy method obtains the starting point of the signal by finding the minimum value of the cumulative energy curve. For signals with a faster amplitude rise at the starting point (i.e., a steeper wave head), the error in identifying the starting point of the signal is smaller, such as Figure 2 However, the local discharge signal generated by the defect discharge in the GIS has a serious attenuation of the high-frequency component after long-distance propagation, which will cause the signal wave head steepness to decrease and the signal amplitude at the signal starting point to change slowly. For signals with slow wave heads, the traditional signal starting point identification method based on the minimum cumulative energy value will lead to large errors, such as Figure 3 As shown. For signals with a slow wave head, there is no corresponding minimum point of the cumulative energy curve at the signal starting point, but the slope of the cumulative energy curve changes significantly near the starting point of the signal. Therefore, the accurate signal starting point position can be extracted based on this slope feature. In response to this, the present invention proposes an improved method for determining the signal starting point based on the change in the slope of the cumulative energy curve;

[0102] like Figure 4 and Figure 5 As shown in FIG, the signal starting point identification results obtained by using the traditional cumulative energy minimum value and the method of the present invention for the same signal are respectively obtained. Figure 4 It shows that the error between the identified signal starting point and the true signal starting point based on the traditional cumulative energy minimum method is large, exceeding 20ns; Figure 5 The results show that the error between the signal starting point identified using the proposed method and the actual signal starting point is significantly reduced, with the error being less than 5 nanoseconds. Accurate signal starting point identification provides a solid foundation for batch identification, analysis, and defect location of partial discharge signals within GIS, enabling more precise automatic defect location.

[0103] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A method for automatically identifying the starting point of a partial discharge pulse signal, characterized in that: include: Obtain the high-frequency electromagnetic wave signal of partial discharge and calculate the corresponding cumulative energy curve; Based on the cumulative energy curve, the initial pulse starting time is determined, two time windows are set based on the initial pulse starting time, and the corresponding reference time points are calculated; Based on the initial pulse starting point and the reference time point, a first slope and a second slope are calculated and compared and judged; According to the comparison and judgment results, the final signal starting time is output; The outputting of the final signal starting point time according to the comparison and judgment result includes: like , then the calculation ends and the output of the final signal starting time is t s ; Otherwise, perform iterative calculation; Wherein, k0 represents the first slope, k1 represents the second slope; The steps of iterative calculation include: Let t s =t s -△t, if t s =0, the calculation ends and the output of the final signal starts at time t s ; Otherwise, the second slope is recalculated and the first slope and the second slope are compared and judged until the starting moment of the final signal is output; Where △t represents the sampling time interval.

2. The method for automatically identifying the starting point of a partial discharge pulse signal according to claim 1, wherein: The obtaining of the partial discharge high-frequency electromagnetic wave signal and the calculation of the corresponding cumulative energy curve include: Read the partial discharge high frequency electromagnetic wave signal, the data format is CSV format, the data length is 2000, The sampling time interval is determined according to the system sampling rate. For electromagnetic wave signals, the corresponding cumulative energy curve is calculated in discrete form. The relevant parameters of the discrete form correspond to the time length of the signal and the sampling time interval.

3. The method for automatically identifying the starting point of a partial discharge pulse signal according to claim 2, wherein: Determining the initial pulse starting time based on the cumulative energy curve includes: The global minimum point of the energy accumulation curve is obtained, and the time coordinate of the minimum point is used as the starting time of the initial pulse of the electromagnetic wave signal.

4. The method for automatically identifying the starting point of a partial discharge pulse signal according to claim 3, wherein: Calculating the first slope and the second slope includes: The first slope represents the average rate of change between the reference time point corresponding to the first time window and the reference time point corresponding to the second time window on the cumulative energy curve.

5. The method for automatically identifying the starting point of a partial discharge pulse signal according to claim 4, wherein: Calculating the first slope and the second slope further includes: The second slope represents the average rate of change between the reference time point corresponding to the first time window and the initial pulse starting point on the cumulative energy curve.

6. A system for automatically identifying the starting point of a partial discharge pulse signal, applying the method according to any one of claims 1 to 5, characterized in that: include: The cumulative energy curve generation module is used to obtain the high-frequency electromagnetic wave signal of partial discharge and calculate the corresponding cumulative energy curve; A reference time point calculation module is used to determine the initial pulse starting time based on the cumulative energy curve, set two time windows based on the initial pulse starting time, and calculate the corresponding reference time point; A starting point identification module is used to calculate the first slope and the second slope based on the initial pulse starting time and the reference time point and compare and judge; According to the result of comparison and judgment, the final signal starting time is output.

7. An electronic device, characterized in that: include: memory and processor; The memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions. When the computer-executable instructions are executed by the processor, the steps of the method according to any one of claims 1 to 5 are implemented.

8. A computer-readable storage medium, characterized in that It stores computer-executable instructions, which, when executed by a processor, implement the steps of the method according to any one of claims 1 to 5.

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