Discharge monitoring system for high-voltage switch cabinet

Abstract

The invention discloses a discharge monitoring system for a high-voltage switch cabinet, relates to the technical field of high-voltage switch cabinets, and solves the related problem of corresponding discharge monitoring precision caused by electromagnetic interference. Discharge data are monitored in real time, if corresponding monitoring data exist, corresponding periodic data are determined, and the corresponding periodic data are sent to the high-voltage switch cabinet; the method comprises the following steps: acquiring periodic data, performing trend analysis on the periodic data, evaluating whether an abnormal pulse exists in a corresponding signal pulse waveform, determining a corresponding waveform frequency based on a normal waveform existing in the corresponding pulse waveform, and adjusting and limiting the waveform frequency of a monitoring end, so that the interference degree of a subsequently monitored signal waveform is reduced to the minimum. Therefore, a better discharge monitoring effect is achieved, and the precision of discharge monitoring can be effectively guaranteed.

Description

Technical Field

[0001] The invention relates to the technical field of high-voltage switch cabinets, and in particular to a discharge monitoring system for high-voltage switch cabinets. Background Art

[0002] High-voltage switchgear is an electrical device used in power systems, mainly used to distribute and control high-voltage electric energy. It can safely connect and disconnect circuits in high-voltage environments, and perform operations such as circuit protection and monitoring. For example, in a substation, the high-voltage switchgear distributes the high-voltage electric energy introduced by the transmission line to different branches to supply different power consumption areas or equipment. At the same time, it can also quickly cut off the circuit when a circuit fault occurs (such as short circuit, overload, etc.) to protect other parts of the power system from damage.

[0003] The application with publication number CN107728025A discloses a system for online monitoring of partial discharge of high-voltage switch cabinet, including ZigBee sensor nodes, wireless communication modules and host computer monitoring modules. The ZigBee sensor nodes include ultrasonic sensor modules, ultrasonic signal conditioning modules, ultra-high frequency sensor modules, ultra-high frequency signal conditioning modules, ultraviolet sensing and conditioning modules and processors. The ultrasonic signal conditioning unit includes an amplifier circuit, a filter circuit and an A / D conversion circuit. The ultraviolet sensing and conditioning module includes an ultraviolet photoelectric conversion unit, a high-voltage drive unit, an I / U conversion unit, a pulse amplification unit and a pulse discrimination unit. The present invention realizes comprehensive and real-time remote monitoring of the switch cabinet status, and has the characteristics of low cost, low false alarm rate, and easy installation.

[0004] During the discharge monitoring process, the high-voltage switchgear generally identifies the relevant signal waveform based on the corresponding monitoring sensor, and then identifies whether there are any related abnormalities in the discharge process based on the specific waveform characteristics of the pulses inside the corresponding signal waveform, and displays the signal in time. However, the existing discharge monitoring methods and systems have many problems and are easily affected by electromagnetic interference, which will lead to related problems with the corresponding discharge monitoring accuracy. Summary of the invention

[0005] In view of the deficiencies in the prior art, the present invention provides a discharge monitoring system for a high-voltage switch cabinet, which solves the problem of corresponding discharge monitoring accuracy caused by electromagnetic interference.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions: A discharge monitoring system for a high-voltage switch cabinet, comprising:

[0007] The historical data analysis end extracts different discharge data and the associated temperature data from the historical completion data, performs feature analysis on the extracted discharge data and temperature data, locks the corresponding feature interval, and transmits the locked feature interval to the feature interval storage end. The specific method is as follows:

[0008] The signal pulse waveform of the discharge data associated with the historical completion data is confirmed. The signal pulse waveform is a preset waveform. The signal pulse waveform associated with each set of different discharge data is confirmed. The amplitude peak value and pulse width of each set of pulses are identified from each set of signal pulse waveforms. Based on this amplitude peak value F i And the pulse width M i , where i represents different pulses, using: Q i =F i ×C1+M i ×C2 confirms the determined value Q of this pulse i , where C1 and C2 are preset fixed coefficient factors;

[0009] According to the order of pulses appearing in the corresponding signal pulse waveform, the confirmed groups of determined values ​​Q i Sorting is performed to lock the determined value sequence belonging to the corresponding signal pulse waveform;

[0010] Then confirm the temperature change data associated with the internal pulse of the corresponding signal pulse waveform from the associated temperature data, and calibrate the temperature data corresponding to the peak point of the corresponding pulse as W i , and sort the temperature data W according to the order of the corresponding determined value sequence i Sorting and confirming the temperature data sequence related thereto;

[0011] Identify adjacent determined values ​​Q in a determined value sequence i The difference is marked as the first difference, and the first difference = Q j+1 -Q j , where j∈i, Q j+1 Represents the next set of determined values ​​of adjacent determined values, whose Q j The previous set of determined values ​​representing adjacent determined values ​​is then identified from the temperature data sequence with a difference value associated therewith, and calibrated as a second difference value, wherein the second difference value = W j+1 -W j , using: second difference ÷ first difference = change trend, confirming several groups of change trends associated with the signal pulse waveform in turn, and locking the change trend interval of the signal pulse waveform;

[0012] Then, the signal pulse waveform associated with other discharge data is processed, the change trend interval is synchronously locked, several groups of determined change trend intervals are merged, and the characteristic interval is locked;

[0013] The characteristic interval storage end stores the confirmed characteristic interval and provides it for extraction by the waveform data processing end;

[0014] The real-time monitoring end performs discharge monitoring on the designated area in the high-voltage switch cabinet. When the discharge data is detected, a set of monitoring cycles is directly determined, and the discharge signal pulse waveform and the associated temperature data detected in this monitoring cycle are monitored, and the monitored cycle data is transmitted to the waveform data processing end;

[0015] The waveform data processing end confirms the trend of the periodic data based on the received periodic data, and then identifies whether there is an abnormal pulse based on the characteristic interval stored in the characteristic interval storage end, and evaluates whether there is an abnormality in the monitoring process of this period. If there is an abnormality, the frequency control end is executed. If there is no abnormality, the pulse is directly confirmed in value to evaluate whether a signal warning is needed through the signal end. The specific method is as follows:

[0016] For the periodic data monitored in this monitoring cycle, the associated discharge signal pulse waveform is extracted, and based on the amplitude peak value and pulse width of the corresponding pulse in the discharge signal pulse waveform, the corresponding pulse determination value Q is determined. k , where k represents different pulses;

[0017] Based on the temperature data associated with the periodic data, the temperature W associated with the corresponding pulse peak point is determined. k , where k represents different pulses;

[0018] Confirm the changing trend of adjacent pulses and determine the value Q k The determined value of a group of pulses after the adjacent pulses is calibrated as Q p+1 , the determined value of the previous group of pulses is calibrated as Q p , where p∈k, the temperature of the latter group of pulses is calibrated as W p+1 , the temperature of the previous group of pulses is calibrated as W p , using: change trend = (Q p+1 -Q p )÷(W p+1 -W p ) determine the changing trend of adjacent pulses;

[0019] Identify whether this change trend belongs to the confirmed characteristic interval. If the change trend belongs to the characteristic interval, the next group of pulses will be calibrated as normal pulses. If the change trend does not belong to the characteristic interval, the next group of pulses will be calibrated as abnormal pulses, and simultaneously identify whether the maximum peak point in the normal waveform of the discharge signal pulse waveform exceeds Y1 (that is, the associated peak value of the maximum peak point>Y1). If it exceeds, the excessive discharge signal is directly generated through the signal end for display. If it does not exceed, the subsequent periodic data is further monitored through the real-time monitoring end, where Y1 is a preset value;

[0020] If there is an abnormal pulse, the frequency control end is executed;

[0021] If there are no abnormal pulses, continue monitoring.

[0022] Preferably, the minimum value of the characteristic interval is the minimum value of several groups of change trend intervals, and the maximum value is the maximum value of several groups of change trend intervals.

[0023] Preferably, the frequency control end, for the abnormal pulse existing in the discharge signal pulse waveform, confirms the associated frequency data of other normal pulses, selects a frequency interval from the confirmed associated frequency data, and then controls the monitoring frequency of the real-time monitoring end according to the confirmed frequency interval, specifically in the following manner:

[0024] Confirm the frequency of the normal pulse confirmed in the discharge signal pulse waveform;

[0025] Confirm the time interval between adjacent normal pulses, mark the confirmed time interval as Tv, where v represents different time intervals, and use Fv=1÷Tv to confirm the frequency data Fv associated with the corresponding time interval;

[0026] Based on the confirmed sets of frequency data Fv, the frequency interval [Fvmin, Fvmax] is locked, and the frequency subsequently monitored by the real-time monitoring terminal is controlled based on the confirmed frequency interval, and only the discharge signal pulse waveform belonging to this frequency interval is monitored.

[0027] Preferably, the monitoring period is a preset period, and the value is 2 minutes.

[0028] The present invention provides a discharge monitoring system for a high-voltage switch cabinet. Compared with the prior art, the present invention has the following beneficial effects:

[0029] The present invention confirms the corresponding discharge data and temperature data from the historical completion data associated with the high-voltage switch cabinet, confirms the characteristic trend associated with the corresponding data from the confirmed discharge data and temperature data, and then locks the corresponding associated characteristic interval based on the confirmed groups of characteristic trends. The characteristic interval is subsequently used as an evaluation standard, so that the discharge monitoring value can be more accurate and a better discharge monitoring effect can be achieved.

[0030] Subsequently, the discharge data is monitored in real time. If there is corresponding monitoring data, the corresponding periodic data is determined, and then a trend analysis is performed on the periodic data to assess whether there are abnormal pulses in the corresponding signal pulse waveform. Based on the normal waveform existing in the corresponding pulse waveform, the corresponding waveform frequency is confirmed, and then the waveform frequency of the monitoring end is adjusted and limited to minimize the interference of the signal waveform monitored subsequently, so as to achieve better discharge monitoring effects, and the accuracy of discharge monitoring can be effectively guaranteed. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 It is a schematic diagram of the principle framework of the present invention;

[0032] Figure 2 It is a schematic diagram of the determination processing flow of discharge monitoring of the present invention. DETAILED DESCRIPTION

[0033] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0034] First embodiment

[0035] See also Figure 1 , the present application provides a discharge monitoring system for a high-voltage switchgear, comprising a historical data analysis terminal, a characteristic interval storage terminal, a real-time monitoring terminal, a waveform data processing terminal, a frequency control terminal and a signal terminal, wherein the historical data analysis terminal, the characteristic interval storage terminal and the waveform data processing terminal are electrically connected from an output node to an input node in sequence, and the real-time monitoring terminal, the waveform data processing terminal and the signal terminal are electrically connected from an output node to an input node, and the waveform data processing terminal, the frequency control terminal and the real-time monitoring terminal are electrically connected from an output node to an input node in sequence;

[0036] Among them, the historical data analysis end extracts different discharge data and the associated temperature data from the historical completion data, and performs feature analysis on the extracted discharge data and temperature data, locks the corresponding feature interval, and transmits the locked feature interval to the feature interval storage end. Specifically, the discharge data is signal pulse waveform data. In the process of different discharge data changes, there is corresponding temperature change data. Therefore, there is an associated change between the discharge data and the temperature data. Therefore, the specific confirmation of the feature interval can be performed to ensure that a better monitoring and calibration effect can be achieved in the future. Among them, the specific method of locking the corresponding feature interval is:

[0037] The signal pulse waveform of the discharge data associated with the historical completion data is confirmed. The signal pulse waveform is a preset waveform that can be directly extracted from the discharge data. The signal pulse waveform associated with each set of different discharge data is confirmed, and the amplitude peak value and pulse width of each group of pulses are identified from each group of signal pulse waveforms (each pulse signal is a waveform that rises and falls rapidly and will drop to the 0 amplitude point. The width associated with the two groups of 0 amplitude points before and after is the pulse width). Based on this amplitude peak value F i And the pulse width M i , where i represents different pulses, using: Q i =F i ×C1+M i ×C2 confirms the determined value Q of this pulse i , where C1 and C2 are preset fixed coefficient factors, and their specific values ​​are determined by the operator based on experience;

[0038] According to the order of pulses appearing in the corresponding signal pulse waveform, the confirmed groups of determined values ​​Q i Sorting is performed to lock the determined value sequence belonging to the corresponding signal pulse waveform;

[0039] Then confirm the temperature change data associated with the internal pulse of the corresponding signal pulse waveform from the associated temperature data, and calibrate the temperature data corresponding to the peak point of the corresponding pulse as W i , and sort the temperature data W according to the order of the corresponding determined value sequence i Sorting and confirming the temperature data sequence related thereto;

[0040] Identify adjacent determined values ​​Q in a determined value sequence i The difference is marked as the first difference, and the first difference = Q j+1 -Q j , where j∈i, Q j+1 Represents the next set of determined values ​​of adjacent determined values, whose Q jThe previous set of determined values ​​representing adjacent determined values ​​is then identified from the temperature data sequence with a difference value associated therewith, and calibrated as a second difference value, wherein the second difference value = W j+1 -W j , using the second difference ÷ first difference = change trend, confirming several groups of change trends associated with the signal pulse waveform in turn, and locking the change trend interval of the signal pulse waveform;

[0041] Then process the signal pulse waveform associated with other discharge data, synchronously lock the change trend interval, merge the determined groups of change trend intervals, lock the characteristic interval (the minimum value of the characteristic interval is the minimum value of the groups of change trend intervals, and the maximum value is the maximum value of the groups of change trend intervals). The historical completion data associated here are all accurate data, and the abnormal data are not recorded in the discharge data associated with the historical completion data. Each time a group of related accurate data is generated, the corresponding characteristic interval will be associated and updated;

[0042] Specifically, when the pulse waveform changes, it is the correlation change between the instantaneous waveforms. When the discharge data gradually increases, the waveform intensity of the corresponding instantaneous waveform will gradually increase. In the actual enhancement process, there are associated temperature changes. Therefore, the pulse and temperature are associated in real time. Based on the changes in the corresponding pulse intensity and temperature values, the corresponding trend changes can be locked. Finally, the corresponding associated characteristic interval is locked, which is convenient for subsequent discharge monitoring and discharge data verification.

[0043] The characteristic interval storage end stores the confirmed characteristic interval and provides it for extraction by the waveform data processing end.

[0044] Second embodiment

[0045] In the specific implementation process of this embodiment, compared with the above-mentioned embodiment, this embodiment mainly focuses on the monitoring process of the corresponding discharge data, and identifies whether the monitored discharge data is subject to relevant interference;

[0046] The real-time monitoring end performs discharge monitoring on the designated area in the high-voltage switch cabinet (using a specific monitoring instrument for monitoring, which can generally be an ultra-high frequency electromagnetic wave sensor or an ultrasonic sensor, etc.). When the discharge data is detected, a set of monitoring cycles is directly determined, and the discharge signal pulse waveform and the associated temperature data monitored in this monitoring cycle are monitored, and the monitored periodic data are transmitted to the waveform data processing end (the periodic data is the data monitored in the monitoring cycle, and the monitoring cycle is a preset cycle, generally 2 minutes);

[0047] Among them, the waveform data processing end confirms the trend of the periodic data based on the received periodic data, and then identifies whether there is an abnormal pulse based on the characteristic interval stored in the characteristic interval storage end, and evaluates whether there is an abnormality in this periodic monitoring process. If there is an abnormality, the frequency control end is executed. If there is no abnormality, the pulse is directly confirmed in value to evaluate whether a signal warning is required through the signal end. Among them, the specific method of evaluating whether there is an abnormality in this periodic monitoring process is:

[0048] Combination Figure 2 , extract the associated discharge signal pulse waveform from the periodic data monitored in this monitoring cycle, and confirm the corresponding pulse determination value Q based on the peak amplitude value and pulse width of the corresponding pulse in the discharge signal pulse waveform k (The determination method is the same as the method of confirming the corresponding pulse determination value at the historical data analysis end), where k represents different pulses;

[0049] Based on the temperature data associated with the periodic data, the temperature W associated with the corresponding pulse peak point is determined. k , where k represents different pulses;

[0050] Confirm the changing trend of adjacent pulses and determine the value Q k The determined value of a group of pulses after the adjacent pulses is calibrated as Q p+1 , the determined value of the previous group of pulses is calibrated as Q p , where p∈k, the temperature of the latter group of pulses is calibrated as W p+1 , the temperature of the previous group of pulses is calibrated as W p , using: change trend = (Q p+1 -Q p )÷(W p+1 -W p ) determine the changing trend of adjacent pulses;

[0051] Identify whether this change trend belongs to the confirmed characteristic interval. If the change trend belongs to the characteristic interval, the latter group of pulses will be calibrated as normal pulses. If the change trend does not belong to the characteristic interval, the latter group of pulses will be calibrated as abnormal pulses. The first group of pulses will generally be directly calibrated as normal pulses due to their small amplitude. And simultaneously identify whether the maximum peak point in the normal waveform of the discharge signal pulse waveform exceeds Y1. If it exceeds, the excessive discharge signal is directly generated through the signal end for display. If it does not exceed, the subsequent periodic data will be monitored through the real-time monitoring end, where Y1 is the preset value;

[0052] If there is an abnormal pulse, the frequency control end is executed;

[0053] If there are no abnormal pulses, continue monitoring.

[0054] Specifically, during the pulse analysis and processing of the corresponding pulse waveform, there will be correlated changes between adjacent pulses, so there will be corresponding temperature changes when they change. When there are abnormal trends in the pulse change and the temperature change, it means that there are other electromagnetic signal interferences. For example, the determined value of the pulse is in an increasing state, but the temperature change is in a decreasing state. Then this type of pulse is an interfered pulse waveform, resulting in a superposition of frequency amplitudes, which causes the pulse to increase. Therefore, in order to achieve the highest accuracy of discharge monitoring, it is necessary to reduce interference to make the discharge monitoring process more accurate.

[0055] The frequency control end, for the abnormal pulse in the discharge signal pulse waveform, confirms the associated frequency data of other normal pulses, selects a frequency interval from the confirmed associated frequency data, and then controls the monitoring frequency of the real-time monitoring end according to the confirmed frequency interval. The specific method of selecting the frequency interval is:

[0056] The abnormal pulses confirmed in the discharge signal pulse waveform are eliminated, and the frequency of the discharge signal pulse waveform after the elimination is confirmed, and the pulses in the discharge signal pulse waveform after the elimination are calibrated as normal pulses;

[0057] Confirm the time interval between adjacent normal pulses (after the abnormal pulses are removed, there will be a corresponding fault, and the normal pulses before and after the fault do not belong to the adjacent normal pulses), calibrate the confirmed time interval as Tv, where v represents different time intervals, and use Fv=1÷Tv to confirm the frequency data Fv associated with the corresponding time interval;

[0058] Based on the confirmed sets of frequency data Fv, the frequency interval [Fvmin, Fvmax] is locked, and the frequency subsequently monitored by the real-time monitoring terminal is controlled based on the confirmed frequency interval, and only the discharge signal pulse waveform belonging to this frequency interval is monitored.

[0059] Third embodiment

[0060] The specific implementation process of this embodiment includes the entire implementation process of the above two groups of embodiments.

[0061] Some of the data in the above formulas are numerically calculated by removing their dimensions. Meanwhile, the contents not described in detail in this specification belong to the prior art known to those skilled in the art.

[0062] The above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. 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 method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. A discharge monitoring system for a high voltage switch cabinet, characterized in that: include: The historical data analysis end extracts different discharge data and the associated temperature data from the historical completion data, performs feature analysis on the extracted discharge data and temperature data, locks the corresponding feature interval, and transmits the locked feature interval to the feature interval storage end; The characteristic interval storage end stores the confirmed characteristic interval and provides it for extraction by the waveform data processing end; The real-time monitoring end performs discharge monitoring on the designated area in the high-voltage switch cabinet. When the discharge data is detected, a set of monitoring cycles is directly determined, and the discharge signal pulse waveform and the associated temperature data detected in this monitoring cycle are monitored, and the monitored cycle data is transmitted to the waveform data processing end; The waveform data processing end confirms the trend of the periodic data based on the received periodic data, and then identifies whether there are abnormal pulses based on the characteristic intervals stored in the characteristic interval storage end, and assesses whether there are abnormalities in this periodic monitoring process. If there are abnormalities, the frequency control end is executed. If there are no abnormalities, the pulse is directly confirmed numerically to assess whether a signal warning is needed through the signal end.

2. A discharge monitoring system for a high voltage switch cabinet according to claim 1, characterized in that: The specific method of locking the corresponding feature interval at the historical data analysis end is: The signal pulse waveform of the discharge data associated with the historical completion data is confirmed. The signal pulse waveform is a preset waveform. The signal pulse waveform associated with each set of different discharge data is confirmed. The amplitude peak value and pulse width of each set of pulses are identified from each set of signal pulse waveforms. Based on this amplitude peak value F i And the pulse width M i , where i represents different pulses, using: Q i =F i ×C1+M i ×C2 confirms the determined value Q of this pulse i , where C1 and C2 are preset fixed coefficient factors; According to the order of pulses appearing in the corresponding signal pulse waveform, the confirmed groups of determined values ​​Q i Sorting is performed to lock the determined value sequence belonging to the corresponding signal pulse waveform; Then confirm the temperature change data associated with the internal pulse of the corresponding signal pulse waveform from the associated temperature data, and calibrate the temperature data corresponding to the peak point of the corresponding pulse as W i , and sort the temperature data W according to the order of the corresponding determined value sequence i Sorting and confirming the temperature data sequence related thereto; Identify adjacent determined values ​​Q in a determined value sequence i The difference is marked as the first difference, and the first difference = Q j+1 -Q j , where j∈i, Q j+1 Represents the next set of determined values ​​of adjacent determined values, whose Q j The previous set of determined values ​​representing adjacent determined values ​​is then identified from the temperature data sequence with a difference value associated therewith, and calibrated as a second difference value, wherein the second difference value = W j+1 -W j , using: second difference ÷ first difference = change trend, confirming several groups of change trends associated with the signal pulse waveform in turn, and locking the change trend interval of the signal pulse waveform; Then, the signal pulse waveform associated with other discharge data is processed, the change trend interval is synchronously locked, several groups of determined change trend intervals are merged, and the characteristic interval is locked.

3. A discharge monitoring system for a high voltage switch cabinet according to claim 2, characterized in that: The minimum value of the characteristic interval is the minimum value of several groups of change trend intervals, and the maximum value thereof is the maximum value of several groups of change trend intervals.

4. A discharge monitoring system for a high voltage switch cabinet according to claim 1, characterized in that: The waveform data processing end evaluates whether there is an abnormality in the monitoring process of this cycle in the following specific ways: For the periodic data monitored in this monitoring cycle, the associated discharge signal pulse waveform is extracted, and based on the amplitude peak value and pulse width of the corresponding pulse in the discharge signal pulse waveform, the corresponding pulse determination value Q is determined. k , where k represents different pulses; Based on the temperature data associated with the periodic data, the temperature W associated with the corresponding pulse peak point is determined. k , where k represents different pulses; Confirm the changing trend of adjacent pulses and determine the value Q k The determined value of a group of pulses after the adjacent pulses is calibrated as Q p+1 , the determined value of the previous group of pulses is calibrated as Q p , where p∈k, the temperature of the latter group of pulses is calibrated as W p+1 , the temperature of the previous group of pulses is calibrated as W p , using: change trend = (Q p+1 -Q p )÷(W p+1 -W p ) determine the changing trend of adjacent pulses; Identify whether this change trend belongs to the confirmed characteristic interval. If the change trend belongs to the characteristic interval, the next group of pulses will be calibrated as normal pulses. If the change trend does not belong to the characteristic interval, the next group of pulses will be calibrated as abnormal pulses. At the same time, identify whether the maximum peak point in the normal waveform of the discharge signal pulse waveform exceeds Y1. If it exceeds, directly generate a discharge excess signal through the signal end for display. If it does not exceed, then the subsequent periodic data will be monitored through the real-time monitoring end, where Y1 is the preset value; If there is an abnormal pulse, the frequency control terminal is executed.

5. A discharge monitoring system for a high voltage switch cabinet according to claim 4, characterized in that: If there are no abnormal pulses, continue monitoring.

6. A discharge monitoring system for a high voltage switch cabinet according to claim 4, characterized in that: The frequency control end confirms the associated frequency data of other normal pulses for the abnormal pulses in the discharge signal pulse waveform, selects a frequency interval from the confirmed associated frequency data, and then controls the monitoring frequency of the real-time monitoring end according to the confirmed frequency interval.

7. A discharge monitoring system for a high voltage switch cabinet according to claim 6, characterized in that: The frequency control end selects the frequency range in the following specific manner: Confirm the frequency of the normal pulse confirmed in the discharge signal pulse waveform; Confirm the time interval between adjacent normal pulses, mark the confirmed time interval as Tv, where v represents different time intervals, and use Fv=1÷Tv to confirm the frequency data Fv associated with the corresponding time interval; Based on the confirmed sets of frequency data Fv, the frequency interval [Fvmin, Fvmax] is locked, and the frequency subsequently monitored by the real-time monitoring terminal is controlled based on the confirmed frequency interval, and only the discharge signal pulse waveform belonging to this frequency interval is monitored.

8. A discharge monitoring system for a high voltage switch cabinet according to claim 1, characterized in that: The monitoring period is a preset period, which is 2 minutes.

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