Online monitoring method and device for ultra-high frequency partial discharge based on discharge point phase distribution characteristics

Abstract

The present invention discloses an online monitoring method and device for ultra-high frequency partial discharge (UHF) based on the phase distribution characteristics of discharge points. The method first receives a wireless UHF signal through an ultra-high frequency receiving antenna and converts the wireless UHF signal into an RF analog signal. The RF analog signal is then amplified, filtered, and amplitude detected to obtain a discharge analog signal. The discharge analog signal is then converted into a digital signal. The digital signal is then preprocessed to reduce noise and optimize the signal-to-noise ratio to obtain a discharge pulse signal. Finally, the discharge pulse signal is subjected to discharge point phase analysis based on the phase distribution characteristics to determine whether an ultra-high frequency partial discharge has occurred and to assess the severity of the ultra-high frequency partial discharge. The present invention monitors whether an ultra-high frequency partial discharge has actually occurred based on the phase distribution characteristics of the discharge point and identifies high phase concentrations of communication interference, ensuring the true and effective analysis of ultra-high frequency partial discharge signals.

Description

Technical Field

[0001] The invention relates to an online monitoring method and device for ultra-high frequency partial discharge based on discharge point phase distribution characteristics, and belongs to electrical information measurement technology. Background Art

[0002] Power plants and substations require extensive use of GIS equipment (Gas-Insulated Metal-Enclosed Switchgear), creating a high demand for UHF partial discharge (PD) monitoring. However, power plants and substations are subject to numerous interference factors, including both electrical and non-electrical interference. These factors can affect UHF PD monitoring results, leading to frequent false alarms and even missed alarms.

[0003] In existing technologies, the main solution for dealing with strong wireless interference such as 5G and LoRA is to add external filters. However, this will result in the inability to fully receive partial discharge signals, which conflicts with the standards of the power industry. For example, the "DL / T1630-2016 Technical Specifications for Ultra-High Frequency Detection of Partial Discharge in Gas-Insulated Metal-Enclosed Switchgear" requires that "the ultra-high frequency detection frequency band for GIS non-discharge should be 300MHz~1500MHz"; and the "QGDW 11304.8-2019 Technical Specifications for Live Detection Instruments for Power Equipment" requires that "the average effective height in the 300MHz~1500MHz frequency band should be no less than 8mm."

[0004] There are some existing technologies that use software filtering methods to process interference and determine whether UHF partial discharge occurs based on signal strength (such as 50Hz or 100Hz signal strength). However, this has great limitations in monitoring UHF partial discharge and preventing false alarms. Summary of the Invention

[0005] Purpose of the invention: In order to overcome the shortcomings of the prior art, the present invention provides an online monitoring method and device for ultra-high frequency partial discharge based on the phase distribution characteristics of the discharge point. Based on the phase distribution characteristics of the discharge point, it is monitored whether ultra-high frequency partial discharge has actually occurred, and the high phase concentration of communication interference is identified to ensure the true and effective analysis of the ultra-high frequency partial discharge signal.

[0006] Technical solution: To achieve the above purpose, the technical solution adopted by the present invention is:

[0007] An online monitoring method for ultra-high frequency partial discharge based on the phase distribution characteristics of discharge points includes the following steps:

[0008] Step 1: Receive the wireless UHF signal through the UHF receiving antenna and convert the wireless UHF signal into an RF analog signal;

[0009] Step 2: Amplify and filter the RF analog signal and perform amplitude detection to obtain a discharge analog signal;

[0010] Step 3: Convert the discharge analog signal into a digital signal;

[0011] Step 4: Preprocess the digital signal to reduce noise, optimize the signal-to-noise ratio, and obtain the discharge pulse signal;

[0012] Step 5: Perform discharge point phase analysis on the discharge pulse signal based on the phase distribution characteristics to determine whether UHF PD occurs and assess the severity of UHF PD.

[0013] Specifically, in Step 4, the digital signal is preprocessed by thresholding, the numerical signal with an amplitude less than the threshold value is judged as noise and assigned to zero, and the digital signal with an amplitude greater than or equal to the threshold value is marked as a discharge pulse signal on the time axis and the amplitude is kept unchanged; that is, the noise signal is processed to 0 to simplify the time domain analysis.

[0014] Specifically, in Step 4, assume that the length of the digital signal is N0 cycles, the time length of each cycle is T, and the total time length is N0T. We need to find the discharge pulse signal from this continuous digital signal with a time length of N0T, remove the basic noise signal, and regard the basic noise signal as white noise. The specific process of screening the discharge pulse signal is: first divide N0T into N segments on average, and the time length of each segment is Calculate the variance of the amplitude for each segment and obtain the variance sequence {σ1,σ2,…,σ N}, the minimum variance of all segments is recorded as σ=min{σ1,σ2,…,σ N}, we can consider the segment with the smallest variance to be pure white noise, and set an appropriate parameter n0 so that within the length range of the digital signal, the probability p that the amplitude of the basic noise signal at the sampling point is greater than n0σ is less than 1. In engineering, it is more reasonable to choose n0=5, which can take into account both the misjudgment caused by noise distribution and the missed judgment caused by the small signal amplitude; set the threshold value to n0σ, and use thresholding processing to preprocess the digital signal. The numerical signal with an amplitude less than the threshold value n0σ is judged as noise and assigned to zero. The digital signal with an amplitude greater than or equal to the threshold value n0σ is marked as a discharge pulse signal on the time axis and the amplitude is kept unchanged. It is preliminarily judged that the discharge pulse signal may be an ultra-high frequency partial discharge.

[0015] Specifically, in Step 5, the discharge point phase analysis of the discharge pulse signal is performed based on the phase distribution characteristics, specifically: assuming that the time length of each cycle is T, there are M sampling points in each cycle, and the time length from the mth sampling point to the start time of the cycle is recorded as the time position t m, the time series of sampling points in one cycle is expressed as {t1,t2,…,t m ,…,t M For a digital signal with a length of N0 cycles, the electric pulse signal of each sampling point is first marked in the time domain by threshold processing. The time series of the electric pulse signal of the i-th cycle is expressed as {y i1 ,y i2 ,…,y im ,…,y iM}; Then superimpose the N0 cycles of electric pulse signals to achieve signal enhancement, and obtain the superimposed electric pulse signal {x1, x2,…, x m ,…,x M}, Then, the superimposed electric pulse signal {x1,x2,...,x m ,…,x M} Perform centering processing in the time domain so that the peak signal is in the middle of the first half cycle or the second half cycle, and express the electric pulse signal after centering processing as {x1',x2',...,x m ',…,x M '}, after this step, the signal strength does not change, only the time position shift occurs, in order to prevent the peak signal from changing to 0 value when it crosses the half-cycle point, which increases the difficulty of calculation; for the electrical pulse signal of the first half cycle (the second half cycle can also be adjusted by adjusting the time offset, and the first and second half cycles can be intermodulated) Calculate the center of gravity t of the discharge pulse group center and radius σ pulse for:

[0016]

[0017] in: Indicates time position With the center of gravity t center The absolute value of the distance on the time axis;

[0018] Based on the time synchronization requirements of power grid transmission, set the time threshold t down , if σ pulse <t down , the discharge pulse signal is judged to be communication interference; based on the correlation between UHF partial discharge and 50Hz power frequency signal, the time threshold σ is set pulse >t up , then the discharge pulse signal is judged to be random interference; the specific judgment is as follows:

[0019] When σ pulse >t up When the UHF PD signal is detected, it is judged that the distribution of the UHF PD signal is too loose and the discharge pulse signal is a random interference.

[0020] When σ pulse <t down When the UHF partial discharge signal is detected, it is judged that the distribution of the UHF partial discharge signal is too concentrated and the discharge pulse signal is communication interference;

[0021] When t down ≤σ pulse ≤t up When the discharge pulse signal is detected, it is judged that it is an ultra-high frequency partial discharge signal, and the severity of the ultra-high frequency partial discharge is evaluated according to the amplitude.

[0022] The above process takes into account that UHF local discharge may appear in both the positive and negative half cycles of the power frequency signal, and performs centering processing on the enhanced electric pulse signal in terms of time position. After the centering processing, we calculate the center of gravity and radius of the discharge pulse group in the first half cycle including the peak signal.

[0023] Specifically, the communication interference is a 5G signal or a LoRA signal.

[0024] A device for implementing the above-mentioned method for online monitoring of ultra-high frequency partial discharge based on the phase distribution characteristics of discharge points, comprising an ultra-high frequency receiving antenna, an ultra-high frequency signal processing module, an analog-to-digital converter, a digital signal preprocessing module and a discharge point phase analysis module; the ultra-high frequency receiving antenna is used to receive wireless ultra-high frequency signals and convert the wireless ultra-high frequency signals into RF analog signals; the ultra-high frequency signal processing module is used to amplify and filter the RF analog signals and perform amplitude detection to obtain discharge analog signals; the analog-to-digital converter is used to convert the discharge analog signals into digital signals; the digital signal preprocessing module is used to preprocess the digital signals to reduce noise and optimize the signal-to-noise ratio to obtain discharge pulse signals; the discharge point phase analysis module performs discharge point phase analysis on the discharge pulse signals based on the phase distribution characteristics to determine whether ultra-high frequency partial discharge has occurred and assess the severity of the ultra-high frequency partial discharge.

[0025] It should be noted that the UHF partial discharge online monitoring device should also be equipped with a communication module to upload detection data, analysis results, early warning information, etc. in a timely manner.

[0026] Specifically, the digital signal preprocessing module processes the digital signal as follows: assuming that the length of the digital signal is N0 cycles, the time length of each cycle is T, and the total time length is N0T, N0T is evenly divided into N segments, and the time length of each segment is Calculate the variance of the amplitude for each segment and obtain the variance sequence {σ1,σ2,…,σ N}, the minimum variance of all segments is recorded as σ=min{σ1,σ2,…,σ N}, set the parameter n0, and set the threshold value to n0σ; use threshold processing to preprocess the digital signal, judge the numerical signal with an amplitude less than the threshold value n0σ as noise and assign it to zero, and mark the digital signal with an amplitude greater than or equal to the threshold value n0σ as a discharge pulse signal on the time axis and keep the amplitude unchanged.

[0027] Specifically, the process of analyzing the discharge pulse signal by the discharge point phase analysis module is as follows: for a digital signal with a length of N0 cycles, M consecutive discharge pulse signals are marked in the time domain by threshold processing, and the positions on the time axis are t1, t2, ..., t M , the amplitudes are y1,y2,…,y M ; Calculate the center of gravity t of the discharge pulse group respectively center and radius σ pulse for:

[0028]

[0029] Among them: r1, r2, …, r M Indicates the time position t1, t2,…, t M With the center of gravity t center The absolute value of the distance on the time axis;

[0030] Based on the time synchronization requirements of power grid transmission, set the time threshold t down , if σ pulse <t down , the discharge pulse signal is judged to be communication interference; based on the correlation between UHF partial discharge and 50Hz power frequency signal, the time threshold σ is set pulse >t up , then the discharge pulse signal is judged to be random interference; the specific judgment is as follows:

[0031] When σ pulse >t up When the UHF PD signal is detected, it is judged that the distribution of the UHF PD signal is too loose and the discharge pulse signal is a random interference.

[0032] When σ pulse <t down When the UHF partial discharge signal is detected, it is judged that the distribution of the UHF partial discharge signal is too concentrated and the discharge pulse signal is communication interference;

[0033] When t down ≤σ pulse ≤t up When the discharge pulse signal is detected, it is judged that it is an ultra-high frequency partial discharge signal, and the severity of the ultra-high frequency partial discharge is evaluated according to the amplitude.

[0034] Specifically, the process of analyzing the discharge pulse signal by the discharge point phase analysis module is as follows: assuming that the time length of each cycle is T, there are M sampling points in each cycle, and the time length from the mth sampling point to the start time of the cycle is recorded as the time position t m , the time series of sampling points in one cycle is expressed as {t1,t2,…,t m ,…,t M For a digital signal with a length of N0 cycles, the electric pulse signal of each sampling point is first marked in the time domain by threshold processing. The time series of the electric pulse signal of the i-th cycle is expressed as {y i1 ,y i2 ,…,y im ,…,y iM}; Then superimpose the N0 cycles of electric pulse signals to obtain the superimposed electric pulse signal {x1, x2,…, x m ,…,x M}, Then, the superimposed electric pulse signal {x1,x2,...,x m ,…,x M} Perform centering processing in the time domain so that the peak signal is in the middle of the first half cycle or the second half cycle, and express the electric pulse signal after centering processing as {x1',x2',…,x m ',…,x M '}; For the first half cycle of the electrical pulse signal Calculate the center of gravity t of the discharge pulse group center and radius σ pulse for:

[0035]

[0036] in: Indicates time position With the center of gravity t center The absolute value of the distance on the time axis;

[0037] Based on the time synchronization requirements of power grid transmission, set the time threshold t down , if σ pulse <t down , the discharge pulse signal is judged to be communication interference; based on the correlation between UHF partial discharge and 50Hz power frequency signal, the time threshold σ is set pulse >t up , then the discharge pulse signal is judged to be random interference; the specific judgment is as follows:

[0038] When σ pulse >t up When the UHF PD signal is detected, it is judged that the distribution of the UHF PD signal is too loose and the discharge pulse signal is a random interference.

[0039] When σ pulse <t down When the UHF partial discharge signal is detected, it is judged that the distribution of the UHF partial discharge signal is too concentrated and the discharge pulse signal is communication interference;

[0040] When t down ≤σ pulse ≤t up When the discharge pulse signal is detected, it is judged that it is an ultra-high frequency partial discharge signal, and the severity of the ultra-high frequency partial discharge is evaluated according to the amplitude.

[0041] Beneficial effects: The present invention provides an online UHF PD monitoring method and device based on the phase distribution characteristics of the discharge point. Based on the phase distribution characteristics of the discharge point, it monitors whether UHF PD actually occurs and identifies the high phase concentration of communication interference, thereby ensuring the real and effective analysis of UHF PD signals. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 Flow chart for the implementation of the method of the present invention;

[0043] Figure 2 This is a typical 5G interference signal pulse sequence spectrum;

[0044] Figure 3 This is a typical UHF partial discharge signal pulse sequence spectrum. DETAILED DESCRIPTION

[0045] The present invention will be described in detail below with reference to the accompanying drawings and specific embodiments.

[0046] like Figure 1 The figure shows an online monitoring method for ultra-high frequency partial discharge based on the phase distribution characteristics of the discharge point. The following describes each step in detail.

[0047] Step 1: Receive the wireless UHF signal through the UHF receiving antenna and convert the wireless UHF signal into an RF analog signal.

[0048] Step 2: Amplify and filter the RF analog signal and perform amplitude detection to obtain a discharge analog signal.

[0049] Step 3: Convert the discharge analog signal into a digital signal.

[0050] Step 4: Preprocess the digital signal to reduce noise, optimize the signal-to-noise ratio, and obtain the discharge pulse signal.

[0051] This step can be regarded as a process of 0-ing the basic noise signal and simplifying the time domain analysis. In this process, we regard the basic noise signal as white noise.

[0052] Assume that the length of the digital signal is N0 cycles, the time length of each cycle is T = 20mS, and the total time length is N0T. We need to find the discharge pulse signal from this continuous digital signal of N0T time length, remove the basic noise signal, and the specific process of screening the discharge pulse signal is: first divide N0T into N = 10 segments, the time length of each segment is Calculate the variance of the amplitude for each segment and obtain the variance sequence {σ1,σ2,…,σ N}, the minimum variance of all segments is recorded as σ=min{σ1,σ2,…,σ N}, we can consider the segment with the smallest variance to be a pure basic noise signal, and set an appropriate parameter n0 so that within the time length of the digital signal, the probability p that the basic noise signal amplitude of the sampling point is greater than n0σ is << 1. In engineering, it is more reasonable to choose n0=5, which can take into account both the misjudgment caused by noise distribution and the missed judgment caused by the small signal amplitude; set the threshold value to n0σ, and use thresholding processing to preprocess the digital signal. The numerical signal with an amplitude less than the threshold value n0σ is judged as noise and assigned to zero. The digital signal with an amplitude greater than or equal to the threshold value n0σ is marked as a discharge pulse signal on the time axis and the amplitude is kept unchanged.

[0053] After this step, it is preliminarily determined that the discharge pulse signal may be ultra-high frequency partial discharge.

[0054] Step 5: Perform discharge point phase analysis on the discharge pulse signal based on the phase distribution characteristics to determine whether UHF PD occurs and assess the severity of UHF PD.

[0055] like Figure 3 As shown in Figure 1, due to the randomness of UHF PD, it presents a certain time width distribution in the time domain; however, due to the strong synchronization of communication signals, external communication interference usually presents a very narrow distribution in the time domain, such as Figure 2 Based on this feature, this case performs discharge point phase analysis on the discharge pulse signal based on the phase distribution feature to determine whether ultra-high frequency partial discharge occurs.

[0056] like Figure 2 The following is a typical 5G interference signal pulse sequence spectrum: Figure 3 The figure shows a typical UHF PD signal pulse train spectrum. It can be seen that UHF PD may occur in both the positive and negative half cycles of the power frequency signal. We consider dividing the cycle length T = 20mS into two parts, first superimposing and strengthening the amplitudes of all discharge pulse signals, then placing the discharge pulse signal at the center of the half cycle, and finally calculating the radius and center of gravity. The specific process is as follows.

[0057] Assume that the time length of each cycle is T = 20mS, there are M sampling points in each cycle, and the time length from the mth sampling point to the start time of the cycle is recorded as time position t m , the time series of sampling points in one cycle is expressed as {t1,t2,…,t m ,…,t M For a digital signal with a length of N0 cycles, the electric pulse signal of each sampling point is first marked in the time domain by threshold processing. The time series of the electric pulse signal of the i-th cycle is expressed as {y i1 ,y i2 ,…,y im ,…,y iM}; Then superimpose the N0 cycles of electric pulse signals to obtain the superimposed electric pulse signal {x1, x2,…, x m ,…,x M}, Then, the superimposed electric pulse signal {x1, x2, ..., x m ,…,x M} Perform centering processing in the time domain so that the peak signal is in the middle of the first half cycle or the second half cycle, and express the electric pulse signal after centering processing as {x1',x2',…,x m ',…,x M '}; For the first half cycle of the electrical pulse signal Calculate the center of gravity t of the discharge pulse group center and radius σ pulse for:

[0058]

[0059]

[0060] in: Indicates time position With the center of gravity t center The absolute value of the distance on the time axis.

[0061] The time synchronization requirement in the power transmission and transformation protocol of the power grid system is usually 30uS. We can set the time threshold t based on the time synchronization requirement of the power grid transmission. down is 2 times 30uS (this multiple can be adjusted), if σ pulse <t down , then the discharge pulse signal is judged to be communication interference; based on the correlation between UHF PD and 50Hz power frequency signal, UHF PD is relatively concentrated in time, so the time threshold σ is set pulse >t up , then the discharge pulse signal is judged to be random interference; the specific judgment is as follows:

[0062] When σ pulse >t up When the UHF PD signal is detected, it is judged that the distribution of the UHF PD signal is too loose and the discharge pulse signal is a random interference.

[0063] When σ pulse <t down When the UHF partial discharge signal is too concentrated, it is judged that the discharge pulse signal is communication interference, and the communication interference is a 5G signal or a LoRA signal;

[0064] When t down ≤σ pulse ≤t up When the discharge pulse signal is detected, it is judged that it is an ultra-high frequency partial discharge signal, and the severity of the ultra-high frequency partial discharge is evaluated according to the amplitude.

[0065] Step 6: Upload test data, analysis results, warning information, etc. via wired or wireless network.

[0066] A device for implementing the above-mentioned method for online monitoring of ultra-high frequency partial discharge based on the phase distribution characteristics of discharge points, comprising an ultra-high frequency receiving antenna, an ultra-high frequency signal processing module, an analog-to-digital converter, a digital signal preprocessing module, a discharge point phase analysis module and a communication module; the ultra-high frequency receiving antenna is used to receive wireless ultra-high frequency signals and convert the wireless ultra-high frequency signals into RF analog signals; the ultra-high frequency signal processing module is used to amplify, filter and perform amplitude detection on the RF analog signals to obtain discharge analog signals; the analog-to-digital converter is used to convert the discharge analog signals into digital signals; the digital signal preprocessing module is used to preprocess the digital signals to reduce noise and optimize the signal-to-noise ratio to obtain discharge pulse signals; the discharge point phase analysis module performs discharge point phase analysis on the discharge pulse signals based on the phase distribution characteristics to determine whether ultra-high frequency partial discharge has occurred and assess the severity of the ultra-high frequency partial discharge; the communication module uploads detection data, analysis results, warning information, etc. via a wired or wireless network.

[0067] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the above embodiments do not limit the present invention in any form, and any technical solutions obtained by equivalent replacement or equivalent transformation fall within the scope of protection of the present invention.

Claims

1. An online monitoring method for ultra-high frequency partial discharge based on the phase distribution characteristics of discharge points, characterized by: The steps include: Step 1: Receive the wireless UHF signal through the UHF receiving antenna and convert the wireless UHF signal into an RF analog signal; Step 2: Amplify and filter the RF analog signal and perform amplitude detection to obtain a discharge analog signal; Step 3: Convert the discharge analog signal into a digital signal; Step 4: Pre-process the digital signal using thresholding. Numerical signals with amplitudes less than the threshold are considered noise and assigned zero. Digital signals with amplitudes greater than or equal to the threshold are marked as discharge pulse signals on the time axis and the amplitudes are kept unchanged. This reduces noise, optimizes the signal-to-noise ratio, and obtains discharge pulse signals. Step 5: Perform discharge point phase analysis on the discharge pulse signal based on the phase distribution characteristics to determine whether UHF PD has occurred and assess the severity of UHF PD. Specifically: Assume that the time length of each cycle is T, and there are M sampling points in each cycle. The time length from the mth sampling point to the start of the cycle is recorded as time position t m , the time series of sampling points in one cycle is expressed as {t1,t2,…,t m ,…,t M For a digital signal with a length of N0 cycles, the electric pulse signal of each sampling point is first marked in the time domain by threshold processing. The time series of the electric pulse signal of the i-th cycle is expressed as {y i1 ,y i2 ,…,y im ,…,y iM }; Then superimpose the N0 cycles of electric pulse signals to obtain the superimposed electric pulse signal {x1, x2,…, x m ,…,x M }, Then, the superimposed electric pulse signal {x1, x2, ..., x m ,…,x M } Perform centering processing in the time domain so that the peak signal is in the middle of the first half cycle or the second half cycle, and express the electric pulse signal after centering processing as {x1',x2',…,x m ',…,x M '}; For the first half cycle of the electrical pulse signal Calculate the center of gravity t of the discharge pulse group center and radius σ pulse for: in: Indicates time position With the center of gravity t center The absolute value of the distance on the time axis; Based on the time synchronization requirements of power grid transmission, set the time threshold t down , if σ pulse <t down , the discharge pulse signal is judged to be communication interference; based on the correlation between UHF partial discharge and 50Hz power frequency signal, the time threshold σ is set pulse >t up , then the discharge pulse signal is judged to be random interference; the specific judgment is as follows: When σ pulse >t up When the UHF PD signal is detected, it is judged that the distribution of the UHF PD signal is too loose and the discharge pulse signal is a random interference. When σ pulse <t down When the UHF partial discharge signal is detected, it is judged that the distribution of the UHF partial discharge signal is too concentrated and the discharge pulse signal is communication interference; When t down ≤σ pulse ≤t up When the discharge pulse signal is detected, it is judged that it is an ultra-high frequency partial discharge signal, and the severity of the ultra-high frequency partial discharge is evaluated according to the amplitude.

2. The method for online monitoring of ultra-high frequency partial discharges based on the phase distribution characteristics of discharge points according to claim 1, characterized in that: In Step 4, suppose the length of the digital signal is N0 cycles, the time length of each cycle is T, the total time length is N0T, and N0T is evenly divided into N segments, the time length of each segment is Calculate the variance of the amplitude for each segment and obtain the variance sequence {σ1,σ2,…,σ N }, the minimum variance of all segments is recorded as σ=min{σ1,σ2,…,σ N }, set the parameter n0, and set the threshold value to n0σ; use threshold processing to preprocess the digital signal, judge the numerical signal with an amplitude less than the threshold value n0σ as noise and assign it to zero, and mark the digital signal with an amplitude greater than or equal to the threshold value n0σ as a discharge pulse signal on the time axis and keep the amplitude unchanged.

3. The method for online monitoring of ultra-high frequency partial discharge based on the phase distribution characteristics of discharge points according to claim 1, characterized in that: The communication interference is a 5G signal or a LoRA signal.

4. An online monitoring device for ultra-high frequency partial discharges based on the phase distribution characteristics of discharge points, characterized by: It includes a UHF receiving antenna, a UHF signal processing module, an analog-to-digital converter, a digital signal preprocessing module and a discharge point phase analysis module; The UHF receiving antenna is used to receive wireless UHF signals and convert the wireless UHF signals into RF analog signals; The UHF signal processing module is used to amplify and filter the RF analog signal and perform amplitude detection to obtain a discharge analog signal; The analog-to-digital converter is used to convert the discharge analog signal into a digital signal; The digital signal preprocessing module is used to preprocess the digital signal, reduce noise, optimize the signal-to-noise ratio, and obtain a discharge pulse signal; The discharge point phase analysis module performs discharge point phase analysis on the discharge pulse signal based on the phase distribution characteristics to determine whether ultra-high frequency partial discharge occurs and evaluate the severity of ultra-high frequency partial discharge; The processing process of the digital signal preprocessing module for the digital signal is as follows: suppose the length of the digital signal is N0 cycles, the time length of each cycle is T, the total time length is N0T, and N0T is evenly divided into N segments, the time length of each segment is Calculate the variance of the amplitude for each segment and obtain the variance sequence {σ1,σ2,…,σ N }, the minimum variance of all segments is recorded as σ=min{σ1,σ2,…,σ N }, set the parameter n0, and set the threshold value to n0σ; use threshold processing to pre-process the digital signal, determine the numerical signal with an amplitude less than the threshold value n0σ as noise and assign it to zero, and mark the digital signal with an amplitude greater than or equal to the threshold value n0σ as a discharge pulse signal on the time axis and keep the amplitude unchanged; The process of analyzing the discharge pulse signal by the discharge point phase analysis module is as follows: Assume that the time length of each cycle is T, and there are M sampling points in each cycle. The time length from the mth sampling point to the start of the cycle is recorded as time position t m , the time series of sampling points in one cycle is expressed as {t1,t2,…,t m ,…,t M For a digital signal with a length of N0 cycles, the electric pulse signal of each sampling point is first marked in the time domain by threshold processing. The time series of the electric pulse signal of the i-th cycle is expressed as {y i1 ,y i2 ,…,y im ,…,y iM }; Then superimpose the N0 cycles of electric pulse signals to obtain the superimposed electric pulse signal {x1, x2,…, x m ,…,x M }, Then, the superimposed electric pulse signal {x1, x2, ..., x m ,…,x M } Perform centering processing in the time domain so that the peak signal is in the middle of the first half cycle or the second half cycle, and express the electric pulse signal after centering processing as {x1',x2',…,x m ',…,x M '}; For the first half cycle of the electrical pulse signal Calculate the center of gravity t of the discharge pulse group center and radius σ pulse for: in: Indicates time position With the center of gravity t center The absolute value of the distance on the time axis; Based on the time synchronization requirements of power grid transmission, set the time threshold t down , if σ pulse <t down , the discharge pulse signal is judged to be communication interference; based on the correlation between UHF partial discharge and 50Hz power frequency signal, the time threshold σ is set pulse >t up , then the discharge pulse signal is judged to be random interference; the specific judgment is as follows: When σ pulse >t up When the UHF PD signal is detected, it is judged that the distribution of the UHF PD signal is too loose and the discharge pulse signal is a random interference. When σ pulse <t down When the UHF partial discharge signal is detected, it is judged that the distribution of the UHF partial discharge signal is too concentrated and the discharge pulse signal is communication interference; When t down ≤σ pulse ≤t up When the discharge pulse signal is detected, it is judged that it is an ultra-high frequency partial discharge signal, and the severity of the ultra-high frequency partial discharge is evaluated according to the amplitude.

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