Primary and secondary integrated ring main unit with intelligent fault location function

Abstract

The present application relates to the technical field of fault location of power systems, and specifically to a primary and secondary fusion ring network cabinet with intelligent fault location function, which includes: a ring network cabinet traveling wave signal acquisition module, which collects traveling wave signals when a transmission line fails; a ring network cabinet traveling wave signal analysis module, which divides the traveling wave signal into equal parts; according to the fluctuation degree of the signal amplitude in the signal segment, combined with the energy spectrum of the signal segment, the mutation coefficient is obtained; according to the frequency domain characteristics and frequency domain shape characteristics of the energy spectrum, the low-frequency concentration of energy is obtained; the filter window size of each sampling point in the signal segment is obtained; the ring network cabinet traveling wave fault location module filters the traveling wave signal, locates the fault, and issues instructions to the primary and secondary fusion switch. The present application aims to effectively remove the pulse noise in the traveling wave signal, retain the detailed information of the fault traveling wave signal, and enhance the accuracy of fault location.

Description

Technical Field

[0001] The present application relates to the technical field of fault location in power systems, and in particular to a primary-secondary integrated ring network cabinet with an intelligent fault location function. Background Art

[0002] In the power system, it is crucial to quickly and accurately locate the line fault location and issue an early warning to improve the power supply reliability of the distribution network. The primary and secondary fusion ring main unit is an important device that combines the advantages of traditional primary and secondary equipment. It can monitor the distribution network in real time and quickly cut off the fault current when a fault occurs, thereby preventing the accident from expanding. Through the traveling wave fault ranging device, the fault section of the distribution line can be quickly located, and the location information can be transmitted to the primary and secondary fusion switch through the communication network. In this way, the fusion switch can perform fault isolation or load transfer operations to reduce the impact of the fault on the entire power grid.

[0003] However, the traveling wave will be disturbed by various noises, especially impulse noise, during its propagation along the line. In order to accurately obtain the arrival time of the wave head in the traveling wave signal to the double-end detection point, the median filter is often used to denoise the signal, but it is usually necessary to set a fixed filter window size. Since the characteristics of the wave head mutation in the pulse noise and the traveling wave signal are similar, the fixed filter window size may cause the wave head mutation information and part of the impulse noise in the traveling wave signal to be smoothed at the same time. This will cause the displacement of the wave head mutation point, thereby affecting the accuracy of the moment when the wave head in the traveling wave signal arrives at the double-end detection point, and further affecting the accuracy of the primary and secondary fusion ring main unit in the fault location of the transmission line. Summary of the invention

[0004] In view of the above, it is necessary to provide a primary-secondary integrated ring network cabinet with intelligent fault positioning function to solve the above technical problems.

[0005] An embodiment of the present application provides a primary-secondary fusion ring network cabinet with a fault intelligent positioning function, wherein the primary-secondary fusion ring network cabinet comprises:

[0006] Ring main unit traveling wave signal acquisition module: used to collect traveling wave signals when a fault occurs in the transmission line;

[0007] Ring main unit traveling wave signal analysis module: used to divide the traveling wave signal into equal parts to obtain several signal segments; according to the fluctuation degree of the signal amplitude in each signal segment, combined with the energy spectrum of each signal segment, the mutation coefficient of each signal segment is obtained; according to the difference between all peak frequencies and the minimum frequency of the energy spectrum, and the difference between the peak area and the corresponding area of ​​the energy spectrum, the low-frequency concentration of energy of each signal segment is obtained; based on the mutation coefficient and the low-frequency concentration of energy, the filter window size of each sampling point in the signal segment is obtained;

[0008] Ring main unit traveling wave fault location module: used to filter the traveling wave signal based on the filter window size corresponding to each signal segment, and locate the fault of the filtered traveling wave signal.

[0009] The step of obtaining the mutation coefficient of each signal segment specifically includes:

[0010] According to the fluctuation degree of the signal amplitude in each signal segment, a fluctuation value of each signal segment is obtained;

[0011] According to the extreme difference value of the frequency in the energy spectrum of each signal segment, the product of the extreme difference value and the fluctuation value is used as the mutation coefficient of each signal segment.

[0012] The fluctuation value of each signal segment is specifically the standard deviation of the signal amplitude in each signal segment.

[0013] The process of obtaining the low-frequency concentration of energy of each signal segment is as follows:

[0014] For each signal segment, obtain the average of the absolute values ​​of the differences between all peak frequencies and the minimum frequency of the energy spectrum; take the ratio of the average to the area ratio as the low-frequency energy concentration of each signal segment; the area ratio is the ratio of the sum of the peak areas of all peaks of the energy spectrum to the total area of ​​the energy spectrum; the total area of ​​the energy spectrum is the area of ​​the region enclosed by the energy spectrum calculated by the integration method and the corresponding horizontal coordinate.

[0015] The filtering window size of each sampling point in the obtained signal segment is specifically:

[0016] The mutation coefficient of the energy spectrum of each signal segment is fused with the low-frequency concentration of energy to obtain the wave head mutation characteristic value of each signal segment; the filter window size of the sampling point is negatively correlated with the wave head mutation characteristic value;

[0017] The filter window size of each sampling point of the i-th signal segment is denoted as R(i), and its formula is: R(i)=r1+round(U(i)×r2), where U(i) represents the wave head mutation characteristic value of the i-th signal segment; round() represents the rounding function; r1 and r2 represent preset values, where the preset values ​​are integers greater than zero.

[0018] The wave head mutation characteristic value of each signal segment is specifically a normalized value of the product of the mutation coefficient of each energy spectrum and the energy low-frequency concentration.

[0019] The specific process of filtering the traveling wave signal is as follows:

[0020] The traveling wave signal is used as the input of the filtering algorithm, and the traveling wave signal is filtered in combination with the filtering window size of the sampling point in each signal segment, and the filtered traveling wave signal is output.

[0021] The filtering algorithm is specifically a median filtering algorithm.

[0022] Wherein, the fault location of the filtered traveling wave signal specifically includes:

[0023] The filtered traveling wave signal is taken as input, and a traveling wave fault distance measuring device is used to obtain the fault location information of the traveling wave signal.

[0024] After the fault is located, instructions are issued to the primary and secondary fusion switches, and the instructions include: fault isolation and load transfer.

[0025] This application has at least the following beneficial effects:

[0026] The present application analyzes the signal mutation points formed by the pulse noise and the wave head in the traveling wave signal, and constructs a mutation coefficient according to the mutation characteristics of the pulse noise and the wave head in the traveling wave signal and the characteristics of the spectrum distribution. The beneficial effect of this application is that the distinction between the signal segments of the signal mutation points formed by the pulse noise and the wave head in the traveling wave signal and the remaining signal segments is improved; by analyzing the distribution difference of the signal energy of the pulse noise and the wave head in the traveling wave signal in the spectrum, based on the energy spectrum of the signal segment, the low-frequency concentration of energy is constructed, the beneficial effect of which is that the recognition ability of the signal mutation points in the traveling wave signal is improved, and the focus is on distinguishing the mutation segments caused by the traveling wave signal wave head and the mutation segments caused by the pulse noise. This can be achieved by analyzing signal characteristics, rate of change and spectrum information to enhance the difference between the two; adaptively obtain the filter window size of each sampling point in the traveling wave signal, and use the obtained filter window size to denoise the traveling wave signal, and use the traveling wave fault distance measurement device to obtain the fault location information of the traveling wave signal based on the denoised traveling wave signal. Its beneficial effect is that it takes into account the pulse noise in the traveling wave signal and the signal distribution of the wave head, sets different filter window sizes for each sampling point in the traveling wave signal, and effectively removes the pulse noise in the traveling wave signal while retaining the detailed information of the fault traveling wave signal as much as possible to reduce the risk of wave head offset caused by excessive smoothing of the wave head mutation. At the same time, it reduces the possibility of mistakenly identifying the retained pulse noise mutation point as the traveling wave head mutation point, thereby improving the accuracy of the primary and secondary fusion ring network cabinet in locating transmission line faults. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 Block diagram of primary and secondary fusion ring network cabinet with intelligent fault location function provided for this application;

[0028] Figure 2 Schematic diagram of the traveling wave signal provided for this application;

[0029] Figure 3 A schematic diagram of a local amplification of a traveling wave signal provided in this application;

[0030] Figure 4 A schematic diagram of a signal after a traveling wave signal is filtered using the traditional median filtering algorithm provided in this application;

[0031] Figure 5 A schematic diagram of a local amplification of a signal after a traveling wave signal is filtered using the traditional median filtering algorithm provided in this application;

[0032] Figure 6 A schematic diagram of a signal after a traveling wave signal is filtered using the improved median filtering algorithm provided in this application;

[0033] Figure 7 A schematic diagram of a local amplification of a signal after the traveling wave signal is filtered by the improved median filtering algorithm provided in this application;

[0034] Figure 8 A specific flowchart for fault location provided in this application. DETAILED DESCRIPTION

[0035] In the description of the embodiments of the present application, words such as "exemplary", "or", "for example" and the like are used to indicate examples, illustrations or descriptions. Any embodiment or design described as "exemplary" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "exemplary", "or", "for example" and the like is intended to present related concepts in a concrete manner.

[0036] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art in the present application. The terms used in the specification of the present application are only for the purpose of describing specific embodiments and are not intended to limit the present application.

[0037] It should also be noted that the terms "first" and "second" in this application and its drawings are used to distinguish similar objects, rather than to describe a specific order or sequence. The method disclosed in the embodiments of the present application or the method shown in the flow chart includes one or more steps for implementing the method. Without departing from the scope of protection of this application, the execution order of multiple steps can be interchanged with each other, and some steps can also be deleted.

[0038] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.

[0039] The specific scheme of the primary and secondary integrated ring network cabinet with intelligent fault location function provided by the present application is described in detail below with reference to the accompanying drawings.

[0040] See also Figure 1 , which shows a block diagram of a primary and secondary integrated ring network cabinet with intelligent fault positioning function provided by an embodiment of the present application. The primary and secondary integrated ring network cabinet includes: a ring network cabinet traveling wave signal acquisition module, a ring network cabinet traveling wave signal analysis module, and a ring network cabinet traveling wave fault positioning module.

[0041] The embodiment of the present application first proposes a primary-secondary fusion ring main unit with a fault intelligent positioning function, which is applied to the technical field of power system fault positioning. The primary-secondary fusion ring main unit includes:

[0042] Ring main unit traveling wave signal acquisition module: collects traveling wave signals when a fault occurs in the transmission line.

[0043] A traveling wave fault ranging device is used to collect traveling wave signals generated when a transmission line fault occurs. When a transmission line fault occurs, the traveling wave fault ranging device will automatically capture the traveling wave signals generated by the line fault and store them automatically. The sampling frequency and sampling time of the traveling wave signals are set to 5kHz and 4 seconds respectively, which can be set by the implementer.

[0044] Among them, the schematic diagram of the traveling wave signal is as follows: Figure 2 As shown in the figure, the box part is the signal position where the wave head of the traveling wave signal is located; the local enlarged schematic diagram of the traveling wave signal is as follows: Figure 3 As shown, specifically Figure 2 The enlarged diagram of the signal in the box. The horizontal axis of the two figures is time, and the vertical axis is voltage amplitude.

[0045] Ring main unit traveling wave signal analysis module: Divide the traveling wave signal equally to obtain several signal segments; obtain the mutation coefficient of each signal segment based on the fluctuation degree of the signal amplitude in each signal segment and the energy spectrum of each signal segment; obtain the low-frequency energy concentration of each signal segment based on the difference between all peak frequencies and the minimum frequency of the energy spectrum, and the difference between the peak area and the corresponding area of ​​the energy spectrum; obtain the filter window size of each sampling point in the signal segment based on the mutation coefficient and the low-frequency energy concentration.

[0046] The present application divides the traveling wave signal into multiple signal segments, sets a larger filtering window for the signal segments suspected of containing pulse noise, and sets a smaller filtering window for the signal segments suspected of containing wave head information, so as to effectively remove the pulse noise in the traveling wave signal and retain the wave head information in the traveling wave signal.

[0047] Specifically, taking the traveling wave signal A as an example for analysis, the traveling wave signal A is first divided into N equal signal segments. In this embodiment, the value of N is 50, which can be set by the implementer.

[0048] Since the wave heads in pulse noise and traveling wave signals both have the characteristic of sudden changes in local signal amplitude, taking the i-th signal segment A(i) in the traveling wave signal A as an example, the standard deviation of the amplitudes of all sampling points in the signal segment A(i) is recorded as the fluctuation value of the signal segment A(i). The larger the standard deviation, the greater the degree of fluctuation, that is, the greater the fluctuation value of each signal segment, the greater the possibility of a signal mutation point appearing in the signal segment A(i).

[0049] Secondly, traveling wave signals are usually caused by fault events in the power system, such as short circuits or ground faults, which will generate signals containing multiple frequency components. These signals will have certain energy attenuation characteristics during the propagation process. The higher the frequency of the fault traveling wave component, the faster its transmission speed, but the corresponding traveling wave energy attenuation is also more serious, making the wave head in the traveling wave signal have a wider spectrum range, and the energy is mainly concentrated in the lower frequency range; while pulse noise is caused by electromagnetic interference or faults and defects in the communication system. The spectrum range of pulse noise is wider, distributed from low frequency to high frequency, and pulse noise usually has a serious tailing effect, which means that in the frequency domain, the energy distribution of pulse noise is not as concentrated as that of traveling wave signals, but is dispersed in a wider frequency range.

[0050] Based on the above analysis, the energy spectrum B(i) of the signal segment A(i) is obtained by Fourier transform, which is used to characterize the distribution of the signal energy in the signal segment A(i) at different frequencies, where the abscissa of the energy spectrum is the frequency and the ordinate is the energy amplitude. The acquisition of the energy spectrum is a well-known technology, and the specific process will not be repeated here.

[0051] The frequency range b(i) in the energy spectrum B(i) is extracted, that is, the extreme difference value of the frequency in the energy spectrum B(i) is calculated, and the product of the extreme difference value and the fluctuation value of the signal segment A(i) is recorded as the mutation coefficient of the signal segment A(i), which is used to characterize the possibility of the signal mutation point formed by the wave head of the pulse noise or the traveling wave signal appearing in the signal segment A(i); the larger the frequency range b(i) of the signal segment A(i) and the greater the fluctuation degree of the amplitude of the sampling point in the signal segment A(i), the more likely it is that the signal mutation point formed by the wave head of the pulse noise or the traveling wave signal will appear in the signal segment A(i), that is, the larger the mutation coefficient.

[0052] Extract all the peaks of the energy spectrum B(i), calculate the peak area of ​​each peak respectively, and obtain the peak frequency corresponding to each peak respectively, that is, the peak frequency represents the frequency corresponding to the peak point of the peak in the energy spectrum B(i); wherein, the extraction of the peaks and the calculation of the areas of the peaks are well-known technologies, and the specific process will not be repeated here.

[0053] Furthermore, based on the difference between all peak frequencies and the minimum frequency of the energy spectrum, and the difference between the peak area and the corresponding area of ​​the spectrum line, the low-frequency concentration of energy of the signal segment A(i) is obtained, which is used to characterize the degree to which the signal energy in the signal segment A(i) is concentrated in the low-frequency part within its frequency range: the mean of the absolute values ​​of the differences between all peak frequencies and the minimum frequency of the energy spectrum B(i) is obtained; the area of ​​the area enclosed by the energy spectrum B(i) and the horizontal axis is calculated by the integration method, and recorded as the total area of ​​the energy spectrum B(i); the proportion of the sum of the peak areas of all wave peaks of the energy spectrum B(i) in the total area is calculated; the ratio of the mean to the proportion is taken as the low-frequency concentration of energy of the signal segment A(i). It should be noted that in the calculation of the ratio, in order to avoid the situation where the denominator is zero, a preset value needs to be added to the denominator, and the preset value is 0.01.

[0054] The total area of ​​the energy spectrum B(i) can represent the total energy of the signal in the signal segment A(i), and the proportion of the peak area of ​​the peak in the total area can measure the contribution of different frequency components in the signal segment A(i) to the signal; the closer the frequencies corresponding to the peak points where the signal energy in the signal segment A(i) is concentrated are to the minimum frequency of the signal segment A(i), and the greater the proportion of the signal energy of the signal segment A(i) at each peak point is, the greater the degree to which the signal energy in the signal segment A(i) is concentrated in the low-frequency part within its frequency range, that is, the greater the low-frequency concentration of energy.

[0055] Furthermore, based on the mutation coefficient of the energy spectrum B(i) and the low-frequency concentration of energy, the wave head mutation characteristic value of the signal segment A(i) is obtained, which is used to characterize the possibility that the signal mutation point appearing in the signal segment A(i) is formed by the wave head of the traveling wave signal; in this embodiment, the normalized value of the product of the mutation coefficient of the energy spectrum B(i) and the low-frequency concentration of energy is used as the mutation characteristic value of the signal segment A(i), and the maximum and minimum value method is used as the normalization method.

[0056] The greater the possibility of a signal mutation point formed by the wave head of a pulse noise or a traveling wave signal appearing in the signal segment A(i), that is, the larger the mutation coefficient, and the greater the degree to which the signal energy in the signal segment A(i) is concentrated in the low-frequency part within its frequency range, the more likely the signal mutation point appearing in the signal segment A(i) is formed by the wave head of a traveling wave signal, that is, the larger the wave head mutation characteristic value.

[0057] According to the wave head mutation characteristic value of the signal segment A(i) and the preset value, the filter window size of each sampling point in the signal segment A(i) is obtained. The filter window size of the sampling point is negatively correlated with the wave head mutation characteristic value. The formula is: R(i)=r1+round(U(i)×r2), where R(i) represents the filter window size of each sampling point in the signal segment A(i); U(i) represents the wave head mutation characteristic value of the signal segment A(i); round() represents the rounding function; r1 and r2 represent the preset values. In order to control the size of the filter window in the median filtering algorithm, r1 and r2 are taken as 3 and 9 respectively. The implementer can adjust it according to the actual situation.

[0058] The greater the possibility that a signal mutation point formed by the wave head of a traveling wave signal appears in the signal segment A(i), that is, the larger U(i) is, the smaller the filtering window of the sampling points in the signal segment A(i) in the median filtering algorithm should be in order to retain the detailed information of the wave head in the traveling wave signal A, that is, the smaller R(i) is; and the smaller U(i) is, the more likely that the signal mutation point appearing in the signal segment A(i) is formed by pulse noise, or the smaller the possibility of a signal mutation point formed by pulse noise or the wave head of a traveling wave signal appears, then in order to effectively remove the pulse noise or other types of noise in the signal segment A(i), the larger the filtering window of the sampling points in the signal segment A(i) in the median filtering algorithm should be, that is, the larger R(i) is.

[0059] The filter window size of each sampling point in the traveling wave signal A is obtained by using the same acquisition method as that of the filter window size of each sampling point in the signal segment A(i).

[0060] Ring main unit traveling wave fault location module: Filters the traveling wave signal based on the filter window size corresponding to each signal segment, and locates the fault of the filtered traveling wave signal.

[0061] The traveling wave signal A is denoised using a median filtering algorithm, wherein the filter window size of each sampling point in the traveling wave signal A is used as the filter window size of each sampling point in the median filtering algorithm to obtain a denoised traveling wave signal A1. The median filtering algorithm is a well-known technology and the specific process will not be repeated here.

[0062] Among them, the signal schematic diagram after the traditional median filtering algorithm filters the traveling wave signal, such as Figure 4 As shown in the figure, the box part is the signal position where the wave head of the traveling wave signal is located; the local enlarged schematic diagram of the signal after the traditional median filtering algorithm filters the traveling wave signal, as shown in Figure 5 As shown, specifically Figure 4 The enlarged diagram of the signal in the box. The horizontal axis of the two figures is time, and the vertical axis is voltage amplitude.

[0063] Furthermore, the signal schematic diagram after the traveling wave signal is filtered by the improved median filtering algorithm is as follows: Figure 6 As shown in FIG. 1 , the box portion is the signal position where the wave head of the traveling wave signal is located; a schematic diagram of a local amplification of the signal after the traveling wave signal is filtered by the improved median filtering algorithm is shown in FIG. Figure 7 As shown, specifically Figure 6 The enlarged diagram of the signal in the box. The horizontal axis of the two figures is time, and the vertical axis is voltage amplitude.

[0064] The denoised traveling wave signal A1 is used as the input of the traveling wave fault ranging device, and the fault position information of the traveling wave signal A is output. The position information refers to the generation position of the traveling wave signal A in the transmission line monitored by the traveling wave fault ranging device, that is, the distance between the fault position of the transmission line and the traveling wave fault ranging device, thereby completing the positioning of the fault position in the monitored transmission line.

[0065] After the fault is located, a command is issued to the primary and secondary fusion switch in the primary and secondary fusion ring network cabinet to perform fault isolation or load transfer operations on the line location where the fault location information is located.

[0066] Among them, the specific flow chart of fault location is as follows: Figure 8 shown.

[0067] In summary, the embodiments of the present application analyze the signal mutation points formed by the pulse noise and the wave head in the traveling wave signal, and construct a mutation coefficient according to the mutation characteristics of the pulse noise and the wave head in the traveling wave signal and the characteristics of the spectrum distribution. The beneficial effect is that the distinction between the signal segments of the signal mutation points formed by the pulse noise and the wave head in the traveling wave signal and the remaining signal segments is improved; by analyzing the distribution difference of the signal energy of the pulse noise and the wave head in the traveling wave signal in the spectrum, based on the energy spectrum of the signal segment, the low-frequency concentration of energy is constructed, which has the beneficial effect of improving the recognition ability of the signal mutation points in the traveling wave signal, with the focus on distinguishing the mutation segments caused by the traveling wave signal wave head from the mutation segments caused by the pulse noise. This can be achieved by analyzing signal characteristics, rate of change and spectrum information to enhance the difference between the two; adaptively obtain the filter window size of each sampling point in the traveling wave signal, and use the obtained filter window size to denoise the traveling wave signal, and use the traveling wave fault distance measurement device to obtain the fault location information of the traveling wave signal based on the denoised traveling wave signal. Its beneficial effect is that it takes into account the pulse noise in the traveling wave signal and the signal distribution of the wave head, sets different filter window sizes for each sampling point in the traveling wave signal, and effectively removes the pulse noise in the traveling wave signal while retaining the detailed information of the fault traveling wave signal as much as possible to reduce the risk of wave head offset caused by excessive smoothing of the wave head mutation. At the same time, it reduces the possibility of mistakenly identifying the retained pulse noise mutation point as the traveling wave head mutation point, thereby improving the accuracy of the primary and secondary fusion ring network cabinet in locating transmission line faults.

[0068] The flowchart and block diagram in the accompanying drawings show the possible architecture, function and operation of the system, method and computer program product according to the embodiment of the present application. In this regard, each box in the flowchart or block diagram can represent a module, a program segment or a part of the code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. In some alternative implementations, the function marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two continuous boxes can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, which can depend on the functions involved. In the description corresponding to the flowchart and the block diagram in the accompanying drawings, the operations or steps corresponding to different boxes can also occur in a different order from the order disclosed in the description, and sometimes there is no specific order between different operations or steps. For example, two continuous operations or steps can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, which can depend on the functions involved. Each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, may be implemented by a dedicated hardware-based system that performs the specified functions or actions, or may be implemented by a combination of dedicated hardware and computer instructions.

[0069] The above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application.

Claims

1. The primary and secondary integrated ring main unit with intelligent fault location function is characterized by: The primary and secondary integrated ring main unit includes: Ring main unit traveling wave signal acquisition module: used to collect traveling wave signals when a fault occurs in the transmission line; Ring main unit traveling wave signal analysis module: used to divide the traveling wave signal into equal parts to obtain several signal segments; according to the fluctuation degree of the signal amplitude in each signal segment, combined with the energy spectrum of each signal segment, the mutation coefficient of each signal segment is obtained; according to the difference between all peak frequencies and the minimum frequency of the energy spectrum, and the difference between the peak area and the corresponding area of ​​the energy spectrum, the low-frequency concentration of energy of each signal segment is obtained; based on the mutation coefficient and the low-frequency concentration of energy, the filter window size of each sampling point in the signal segment is obtained; Ring main unit traveling wave fault location module: used to filter the traveling wave signal based on the filter window size corresponding to each signal segment, and locate the fault of the filtered traveling wave signal; The step of obtaining the mutation coefficient of each signal segment comprises: According to the fluctuation degree of the signal amplitude in each signal segment, a fluctuation value of each signal segment is obtained; According to the range value of the intermediate frequency of the energy spectrum of each signal segment, the product of the range value and the fluctuation value is used as the mutation coefficient of each signal segment; The fluctuation value of each signal segment is specifically the standard deviation of the signal amplitude in each signal segment; The process of obtaining the low-frequency concentration of energy of each signal segment is as follows: For each signal segment, obtain the average of the absolute values ​​of the differences between all peak frequencies and the minimum frequency of the energy spectrum; take the ratio of the average to the area ratio as the low-frequency energy concentration of each signal segment; the area ratio is the ratio between the sum of the peak areas of all wave peaks of the energy spectrum and the total area of ​​the energy spectrum; the total area of ​​the energy spectrum is the area of ​​the region enclosed by the energy spectrum calculated by the integration method and the corresponding horizontal coordinate; The filtering window size of each sampling point in the obtained signal segment is specifically: The mutation coefficient of the energy spectrum of each signal segment is fused with the low-frequency concentration of energy to obtain the wave head mutation characteristic value of each signal segment; the filter window size of the sampling point is negatively correlated with the wave head mutation characteristic value; The wave head mutation characteristic value of each signal segment is specifically a normalized value of the product of the mutation coefficient of each energy spectrum and the energy low-frequency concentration.

2. The primary and secondary integrated ring main unit with intelligent fault location function as claimed in claim 1, characterized in that: The specific process of filtering the traveling wave signal is as follows: The traveling wave signal is used as the input of the filtering algorithm, and the traveling wave signal is filtered in combination with the filtering window size of the sampling point in each signal segment, and the filtered traveling wave signal is output.

3. The primary and secondary integrated ring main unit with intelligent fault location function as claimed in claim 2, characterized in that: The filtering algorithm is specifically a median filtering algorithm.

4. The primary and secondary integrated ring main unit with intelligent fault location function as claimed in claim 1, characterized in that: The fault location of the filtered traveling wave signal specifically includes: The filtered traveling wave signal is taken as input, and a traveling wave fault distance measuring device is used to obtain the fault location information of the traveling wave signal.

5. The primary and secondary integrated ring main unit with intelligent fault location function as claimed in claim 1, characterized in that: After the fault is located, an instruction is issued to the primary and secondary fusion switches, the instruction including: fault isolation or load transfer.

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