Discharge point phase distribution characteristic-based ultrahigh frequency partial discharge on-line monitoring method and device

Abstract

The invention discloses an ultrahigh frequency partial discharge online monitoring method and device based on discharge point phase distribution characteristics, and the method comprises the steps: receiving a wireless ultrahigh frequency signal through an ultrahigh frequency receiving antenna, and converting the wireless ultrahigh frequency signal into an RF analog signal; the RF analog signal is amplified, filtered and subjected to amplitude detection, and a discharge analog signal is obtained; converting the discharge analog signal into a digital signal; the digital signal is preprocessed, noise is reduced, the signal-to-noise ratio is optimized, and a discharge pulse signal is obtained; and finally, carrying out discharge point phase analysis on the discharge pulse signal based on the phase distribution characteristics, judging whether ultrahigh-frequency partial discharge occurs, and evaluating the severity of the ultrahigh-frequency partial discharge. According to the method, whether ultrahigh-frequency partial discharge occurs actually is monitored based on the phase distribution characteristics of the discharge points, and the high-phase concentration degree of communication interference is identified, so that the ultrahigh-frequency partial discharge signals can be analyzed actually and effectively.

Description

Technical Field

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

[0002] In power plants or substations, GIS equipment (gas-insulated metal-enclosed switchgear) is widely used, so the demand for UHF partial discharge monitoring is relatively high. However, there are many interference factors at power plants or substations, including electrical signal interference and non-electrical signal interference. These interference factors will affect the monitoring results of UHF partial discharge, resulting in frequent false alarms and sometimes even missed alarms.

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

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

[0005] Purpose of the invention: In order to overcome the deficiencies in the prior art, the present invention provides an online monitoring method and device for UHF partial discharge based on the phase distribution characteristics of the discharge point. The method and device can monitor whether UHF partial discharge actually occurs based on the phase distribution characteristics of the discharge point, and identify the high phase concentration of communication interference, to ensure the real and effective analysis of the UHF 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 comprises 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 partial discharge occurs and evaluate the severity of UHF partial discharge.

[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 the continuous digital signal of N0T time length, 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 The variance of the amplitude is calculated for each segment, and 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 of the basic noise signal amplitude at the sampling point being greater than n0σ is greater 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 threshold processing to pre-process 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 a UHF 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 electrical pulse signal of each sampling point is first marked in the time domain by threshold processing. The time series of the electrical pulse signal of the ith cycle is expressed as {y i1 ,y i2 ,…,y im ,…,y iM}; Then superimpose the N0 cycles of electrical pulse signals to achieve signal enhancement, and obtain the superimposed electrical pulse signal {x1, x2, …, x m ,…,x M}, Next, the superimposed electrical 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 the electric pulse signal after centering processing is represented as {x1',x2',...,x m ',…,x M '}, after this step, the signal strength does not change, only the time position shifts, in order to prevent the peak signal from changing to 0 value just across 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, 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 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, the time threshold t is set. 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 industrial frequency signal, and the enhanced electric pulse signal is centered in 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 UHF partial discharge online monitoring method based on the phase distribution characteristics of the discharge point, comprising 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 a wireless UHF signal and convert the wireless UHF signal into an RF analog signal; 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 UHF partial discharge occurs and evaluate the severity of the UHF 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 processing process of the digital signal preprocessing module for the digital signal is as follows: assuming that 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, and the time length of each segment is The variance of the amplitude is calculated for each segment, and the variance sequence {σ1,σ2,…,σ N}, the minimum variance of all segments is recorded as σ = min{σ1,σ2,…,σ N}, set parameter n0, 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 continuous 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] Where: r1, r2, …, r M Indicates the time position t1, t2, ..., t M With 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, the time threshold t is set. 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 electrical pulse signal of each sampling point is first marked in the time domain by threshold processing. The time series of the electrical pulse signal of the ith cycle is expressed as {y i1 ,y i2 ,…,y im ,…,y iM}; then superimpose the N0 cycles of electrical pulse signals to obtain the superimposed electrical pulse signal {x1, x2, …, x m ,…,x M}, Next, the superimposed electrical 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 the electric pulse signal after centering processing is represented as {x1',x2',…,x m ',…,x M '}; For the electrical pulse signal of the first half cycle Calculate the center of gravity t of the discharge pulse group center and radius σ pulse for:

[0035]

[0036] in: Indicates time position With 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, the time threshold t is set. 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 UHF partial discharge online monitoring method and device based on the phase distribution characteristics of the discharge point provided by the present invention can monitor whether the UHF partial discharge has actually occurred based on the phase distribution characteristics of the discharge point, and identify the high phase concentration of communication interference, which can ensure the real and effective analysis of the UHF partial discharge signal. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 1 is a flow chart for implementing 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 is 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, which is described in detail below in combination with each step.

[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 a 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 on average, and the time length of each segment is The variance of the amplitude is calculated for each segment, and 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 of the basic noise signal amplitude at the sampling point being 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 pre-process the digital signal. The numerical signal with an amplitude less than the threshold value n0σ is judged as noise and assigned to zero, and 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 an 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 partial discharge occurs and evaluate the severity of UHF partial discharge.

[0055] like Figure 3 As shown in the figure, 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 such a 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 partial discharge signal pulse sequence spectrum. It can be seen that UHF partial discharge 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 electrical pulse signal of each sampling point is first marked in the time domain by threshold processing. The time series of the electrical pulse signal of the ith cycle is expressed as {y i1 ,y i2 ,…,y im ,…,y iM}; then superimpose the N0 cycles of electrical pulse signals to obtain the superimposed electrical pulse signal {x1, x2, …, x m ,…,x M}, Next, the superimposed electrical 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 the electric pulse signal after centering processing is represented as {x1',x2',…,x m ',…,x M '}; For the electrical pulse signal of the first half cycle 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 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 twice 30uS (this multiple can be adjusted), if σ pulse <t down , 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 determined to be too concentrated, the discharge pulse signal is communication interference, and the communication interference is a 5G signal or a LoRA signal, etc.;

[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 the detection data, analysis results, warning information, etc. through a wired or wireless network.

[0066] A device for implementing the above-mentioned UHF partial discharge online monitoring method based on the phase distribution characteristics of the discharge point, comprising a UHF receiving antenna, a UHF signal processing module, an analog-to-digital converter, a digital signal preprocessing module, a discharge point phase analysis module and a communication 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 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, reduce noise, optimize the signal-to-noise ratio, and 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, determines whether UHF partial discharge occurs, and evaluates the severity of UHF partial discharge; the communication module uploads detection data, analysis results, warning information, etc. through 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 solution obtained by equivalent replacement or equivalent transformation falls within the protection scope 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: Preprocess the digital signal to reduce noise, optimize the signal-to-noise ratio, and obtain the discharge pulse signal; Step 5: Perform discharge point phase analysis on the discharge pulse signal based on the phase distribution characteristics to determine whether UHF partial discharge occurs and evaluate the severity of UHF partial discharge.

2. 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: In Step 4, the digital signal is preprocessed by threshold processing, 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.

3. The method for online monitoring of ultra-high frequency partial discharge based on the phase distribution characteristics of discharge points according to claim 2 is characterized in that: In Step 4, assume that 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, and the time length of each segment is The variance of the amplitude is calculated for each segment, and the variance sequence {σ1,σ2,…,σ N }, the minimum variance of all segments is recorded as σ = min{σ1,σ2,…,σ N }, set parameter n0, 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.

4. The method for online monitoring of ultra-high frequency partial discharge based on the phase distribution characteristics of discharge points according to claim 2, characterized in that: In the Step 5, the discharge point phase analysis is performed on the discharge pulse signal based on the phase distribution characteristics, 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 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 electrical pulse signal of each sampling point is first marked in the time domain by threshold processing. The time series of the electrical pulse signal of the ith cycle is expressed as {y i1 ,y i2 ,...,y im ,…,y iM }; then superimpose the N0 cycles of electrical pulse signals to obtain the superimposed electrical pulse signal {x1, x2, …, x m ,…,x M }, Next, the superimposed electrical 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 the electric pulse signal after centering processing is represented as {x1',x2',…,x m ',…,x M '}; For the electrical pulse signal of the first half cycle Calculate the center of gravity t of the discharge pulse group center and radius σ pulse for: in: Indicates time position With 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, the time threshold t is set. 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.

5. The method for online monitoring of ultra-high frequency partial discharge based on the phase distribution characteristics of discharge points according to claim 4 is characterized in that: The communication interference is a 5G signal or a LoRA signal.

6. An online monitoring device for ultra-high frequency partial discharge based on the phase distribution characteristics of discharge points, characterized in that: 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, determines whether ultra-high frequency partial discharge occurs, and evaluates the severity of the ultra-high frequency partial discharge.

7. The UHF partial discharge online monitoring device based on the phase distribution characteristics of the discharge point according to claim 6 is characterized in that: The processing process of the digital signal preprocessing module for the digital signal is as follows: assuming that 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 The variance of the amplitude is calculated for each segment, and the variance sequence {σ1,σ2,…,σ N }, the minimum variance of all segments is recorded as σ = min{σ1,σ2,…,σ N }, set parameter n0, 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.

8. The UHF partial discharge online monitoring device based on the phase distribution characteristics of the discharge point according to claim 6, characterized in that: 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 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 electrical pulse signal of each sampling point is first marked in the time domain by threshold processing. The time series of the electrical pulse signal of the ith cycle is expressed as {y i1 ,y i2 ,…,y im ,…,y iM }; then superimpose the N0 cycles of electrical pulse signals to obtain the superimposed electrical pulse signal {x1, x2, ..., x m ,…,x M }, Next, the superimposed electrical 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 the electric pulse signal after centering processing is represented as {x1',x2',...,x m ',…,x M '}; For the electrical pulse signal of the first half cycle Calculate the center of gravity t of the discharge pulse group center and radius σ pulse for: in: Indicates time position With 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, the time threshold t is set. 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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