Intelligent detection method for discharge part of high-voltage transmission line

Abstract

The invention relates to the field of discharge part detection, and particularly discloses a high-voltage transmission line discharge part intelligent detection method, which comprises the following steps of: arranging UHF (Ultra High Frequency) sensors on a plurality of side-by-side high-voltage transmission lines at equal intervals in a staggered manner, and monitoring signals in real time; screening effective signals based on the signal amplitude, and judging whether the signals are partial discharge signals or not through pulse feature matching; after a discharge range is preliminarily determined based on partial discharge signal intensity, a plurality of triangular sensor arrays are constructed, a time difference positioning method is adopted to calculate and determine suspected discharge points corresponding to the sensor arrays, and discharge parts and intensity thereof are determined through spatial clustering analysis; and finally, collecting a visible light image of a discharge part, extracting physical defect information, analyzing the defect degree, evaluating the discharge severity by combining the discharge intensity and the defect degree, and generating a detection report. The method can effectively eliminate interference, improves the positioning precision and reliability, and achieves the efficient detection and evaluation of the discharge part of the high-voltage transmission line.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of discharge site detection, and relates to an intelligent discharge site detection method for high-voltage transmission lines. BACKGROUND

[0002] During long-term operation, high-voltage transmission lines are prone to partial discharge due to factors such as insulation aging, mechanical damage, and environmental pollution. Discharge not only accelerates the deterioration of insulation materials, but also may cause line faults or even power outage accidents, seriously affecting the safe and stable operation of the power grid. Therefore, it is of great practical significance to accurately and efficiently detect and locate the discharge site of high-voltage transmission lines.

[0003] Currently, time difference positioning (TDOA) is mostly used for discharge positioning. The basic principle is to measure the time difference of discharge signals reaching different sensors, and combine the electromagnetic wave propagation speed to calculate the spatial position of the discharge point.

[0004] In the prior art, one-dimensional point positioning is mostly used, that is, sensors are only arranged on a single transmission line, and the discharge point on the line is located by the time difference between two sensors. However, this method does not consider the interference of discharge on different transmission lines on the sensors, and the positioning result is easily affected by multipath effect and cross interference, and the reliability is insufficient. In addition, the data support of a single sensor group is limited, and the anti-interference ability is weak, which is difficult to meet the discharge detection demand in complex electromagnetic environment, and there is a high risk of false positives and false negatives. SUMMARY

[0005] To solve the above problems, the present application provides an intelligent discharge site detection method for high-voltage transmission lines, and the specific technical scheme is as follows: an intelligent discharge site detection method for high-voltage transmission lines, comprising the following steps: S1, sensor arrangement: evenly arranging a plurality of UHF sensors in an equal-interval staggered manner on a plurality of high-voltage transmission lines arranged side by side, numbering and recording the positions of the UHF sensors.

[0006] S2, discharge identification: real-time monitoring of the original signals captured by each UHF sensor, screening out valid signals according to the signal amplitude, judging whether it is a partial discharge signal based on the pulse characteristics of the valid signals, if yes, triggering an early warning and entering step S3, if not, continuing to monitor the sensor signals.

[0007] S3, discharge positioning: preliminarily determining the discharge occurrence range according to the intensity of the partial discharge signal, constructing a plurality of triangular sensor arrays within the discharge occurrence range, analyzing the suspected discharge points corresponding to each sensor array using time difference positioning method, determining the discharge site according to the analysis results of the suspected discharge points of each sensor array, and determining the discharge intensity of the discharge site.

[0008] S4, severity evaluation: visible light images of the discharge part are collected by the unmanned aerial vehicle, physical defect information is extracted and defect degree is analyzed, the discharge severity is evaluated in combination with the defect degree of the discharge part and the discharge intensity, and a detection report is generated.

[0009] The specific analysis process of step S1 is as follows: S11: according to the measurable frequency of the UHF sensor, the electromagnetic signal attenuation characteristic and the positioning accuracy requirement, the spacing between the two adjacent UHF sensors is determined as the layout spacing.

[0010] S12: each power transmission line is sorted in order from one side to the other side.

[0011] S13: a plurality of UHF sensors are uniformly laid out on the first power transmission line according to the layout spacing.

[0012] S14: according to the position of the UHF sensor on the first power transmission line, a plurality of UHF sensors are uniformly laid out on the second power transmission line in a staggered manner according to the layout spacing.

[0013] S15: according to the position of the UHF sensor on the second power transmission line, a plurality of UHF sensors are uniformly laid out on the third power transmission line in a staggered manner according to the layout spacing, wherein the staggered direction of the UHF sensor on the third power transmission line relative to the UHF sensor on the second power transmission line is the same as or opposite to the staggered direction of the UHF sensor on the second power transmission line relative to the UHF sensor on the first power transmission line.

[0014] S16: according to the method of S13 to S15, the UHF sensors are laid out on each power transmission line in turn.

[0015] S17: all UHF sensors are numbered, and the position information of each sensor is recorded, including the number of the power transmission line to which it belongs and the position coordinates on the power transmission line.

[0016] The specific analysis process of step S2 for screening effective signals is as follows: the amplitude of the original signal captured by the UHF sensor is obtained, and compared with the preset signal amplitude threshold value, if the amplitude of the original signal is greater than the signal amplitude threshold value, the original signal is determined as an effective signal, otherwise it is determined as a noise signal.

[0017] The specific analysis process of step S2 for determining whether it is a partial discharge signal is as follows: based on the phase resolution partial discharge spectrum of the effective signal, the pulse characteristics are extracted, including pulse phase distribution characteristics, pulse amplitude distribution characteristics, pulse repetition rate and pulse cross-correlation coefficient.

[0018] The extracted pulse characteristics are compared with the typical pulse characteristics of the pre-stored partial discharge signals in the database, and the degree of coincidence between the two is analyzed.

[0019] The matching degree is compared with a preset matching degree threshold. If the matching degree is greater than or equal to the threshold, the valid signal is determined to be a partial discharge signal; otherwise, it is determined to be an interference signal.

[0020] The specific process of analyzing the intensity of the partial discharge signal in step S3 is as follows: obtain the amplitude index and energy index of the partial discharge signal. The amplitude index includes the peak amplitude and the equivalent apparent discharge quantity, and the energy index includes the pulse energy and the average power.

[0021] The amplitude and energy indices are input into a preset signal strength evaluation model to determine the intensity of the partial discharge signal. The signal strength evaluation model includes a quantitative mapping relationship between the amplitude and energy indices and the signal strength.

[0022] The specific analysis process for determining the discharge range in step S3 is as follows: statistically analyze all UHF sensors that captured partial discharge signals and their corresponding partial discharge signal intensities.

[0023] Extract the numerical range of partial discharge signal intensity corresponding to each intensity level from the pre-stored database.

[0024] The areas covered by the UHF sensor, whose partial discharge signal intensity is located in the ranges of high intensity, medium intensity, and low intensity, are respectively denoted as the discharge core region, transition region, and edge region.

[0025] The core region, transition region, and edge region of the discharge are integrated to determine the final discharge range.

[0026] The specific process of analyzing the suspected discharge points corresponding to each sensor array in step S3 is as follows: extract the spatial model of multiple parallel high-voltage transmission lines pre-stored in the database, cut out the high-voltage transmission line spatial model of the section corresponding to the discharge occurrence range, and mark the position of all UHF sensors within that range.

[0027] Three non-collinear UHF sensors in space are defined as a triangular sensor array.

[0028] All UHF sensors within the discharge range are combined in triplicate to construct multiple triangular sensor arrays: within the discharge range there are Calculate the number of combinations for each UHF sensor. This means selecting 3 elements from N distinct elements. Each selection corresponds to a potential triangular sensor array. The spatial positions of the three selected UHF sensors are checked to ensure they are not collinear. If they are not collinear, the three UHF sensors are defined and constructed into a triangular sensor array.

[0029] For each triangular sensor array, the time difference between every two sensors in the array capturing the same partial discharge signal is obtained. Combined with the electromagnetic wave propagation speed, the time difference positioning method is used to calculate and determine one or more suspected discharge points corresponding to the triangular sensor array.

[0030] The specific process of determining the suspected discharge point corresponding to the triangular sensor array using the time difference positioning method is as follows: The three sensors within the triangular sensor array are respectively denoted as... And obtain the time when each sensor captures the same partial discharge signal.

[0031] calculate and Time difference of signal acquisition Combined with the speed of electromagnetic wave propagation Through formula Calculate the discharge point To the sensor and Distance difference ,by , Draw a hyperbola that satisfies the distance difference around the focus, and denote it as the first hyperbola.

[0032] Similarly, based on , Time difference of signal acquisition and , Time difference of signal acquisition Draw the second and third hyperbolas respectively.

[0033] The intersection of the three hyperbolas is determined as the suspected discharge point corresponding to the triangular sensor array. There can be one or more suspected discharge points, and the spatial coordinates of the suspected discharge points are recorded.

[0034] The specific process of determining the discharge location and analyzing its discharge intensity in step S3 is as follows: T1: In the high-voltage transmission line spatial model of the section corresponding to the discharge occurrence range, mark all the suspected discharge points corresponding to each triangular sensor array, and remove abnormal points that are obviously far away from the transmission line according to preset rules to obtain the optimized spatial distribution of suspected discharge points.

[0035] T2: If the suspected discharge points converge at a single location in space, then that point is directly identified as the discharge site; otherwise, proceed to T3.

[0036] T3: Calculate the spatial distance between each suspected discharge point. If the distance between any two points is less than the set spatial distance threshold, then the two points are determined to belong to the same discharge point group.

[0037] Count the number of all discharge point groups.

[0038] If there is only one discharge point group, the geometric center of the point group is determined as the discharge site, otherwise, go to T4.

[0039] T4: Count the number of suspected discharge points in each discharge point group, and calculate the average number of points contained in all point groups.

[0040] If the number of points in a discharge point group is higher than the average and the excess reaches a set threshold, the point group is defined as the main discharge point group.

[0041] Count the number of main discharge point groups: if there is only one main point group, the center point is determined as the discharge site, if there are two main point groups, the midpoint of the line connecting the two main point group center points is determined as the discharge site, if there are more than two main point groups, go to T5.

[0042] T5: Connect the center points of each main discharge point group in turn to form a polygonal region, and determine the geometric center of the polygonal region as the discharge site.

[0043] T6: Determine the highest intensity in the partial discharge signal captured by all UHF sensors in the discharge occurrence range as the discharge intensity of the discharge site.

[0044] The specific analysis process of step S4 is: collecting a visible light image of the area where the discharge site is located by the unmanned aerial vehicle, and extracting physical defect information from the image based on image processing technology, the physical defect information includes deformation amount and damage area.

[0045] According to the preset relationship function between the deformation amount and the damage area and the defect degree, the defect degree of the discharge site is determined.

[0046] The defect degree and the discharge intensity are weighted and fused to analyze and obtain a quantitative evaluation result of the discharge severity.

[0047] Compared with the prior art, the intelligent detection method for discharge sites of high-voltage transmission lines has the following advantages: 1. The present application sets the sensor layout interval and staggered mode scientifically, taking into account the monitoring sensitivity and positioning accuracy, avoiding blind spots, and improving the coverage ability and monitoring efficiency of long line sections.

[0048] 2. The present application arranges UHF sensors on multiple transmission lines in an equidistant staggered manner to form multiple triangular sensor arrays, and uses time difference positioning method for multi-dimensional space positioning, which effectively avoids single path interference and significantly improves the positioning accuracy and result reliability of discharge points.

[0049] 3. The application adopts a combination of signal amplitude threshold screening and pulse feature matching to effectively distinguish partial discharge signals from background noise or lightning interference signals, greatly reducing the misjudgment rate and improving the anti-interference performance of the system.

[0050] 4. The application combines the discharge intensity during discharge and the physical defect information after discharge to generate a quantitative evaluation result of discharge severity through weighted fusion analysis, providing a more comprehensive and objective basis for operation and maintenance decisions. BRIEF DESCRIPTION OF DRAWINGS

[0051] In order to more clearly illustrate the technical solutions of the embodiments of the application, the following will briefly introduce the drawings needed to be used in the description of the embodiments. Obviously, the drawings in the following description are only some embodiments of the application, and for those skilled in the art, other drawings can also be obtained without creative labor based on these drawings.

[0052] Figure 1 The figure is a schematic diagram of the method of the application.

[0053] Figure 2 The figure is a schematic diagram of the sensor layout of the application.

[0054] Figure 3 The figure is a flowchart of identifying partial discharge signals of the application. DETAILED DESCRIPTION

[0055] The technical solutions in the embodiments of the application will be described clearly and completely in the following with reference to the drawings in the embodiments of the application. Obviously, the described embodiments are only some embodiments of the application, not all the embodiments. Based on the embodiments in the application, all other embodiments obtained by those skilled in the art without creative labor are within the protection scope of the application.

[0056] Please refer to Figure 1 The application provides an intelligent detection method for discharge parts of high-voltage transmission lines, which comprises the following steps: S1, sensor layout: uniformly laying a plurality of UHF sensors in an equal-interval staggered manner on a plurality of high-voltage transmission lines arranged side by side, numbering and recording the positions of the UHF sensors.

[0057] As a preferred solution, please refer to Figure 2 The specific analysis process of step S1 is as follows: S11: according to the measurable frequency of the UHF sensor, the electromagnetic signal attenuation characteristic and the positioning accuracy requirement, the interval between the two adjacent UHF sensors is determined as the layout interval.

[0058] S12: sorting the transmission lines in order from one side to the other side.

[0059] S13: uniformly arranging a plurality of UHF sensors on the first power transmission line according to the arrangement interval.

[0060] S14: uniformly arranging a plurality of UHF sensors on the second power transmission line according to the arrangement interval in a staggered manner according to the positions of the UHF sensors on the first power transmission line.

[0061] S15: uniformly arranging a plurality of UHF sensors on the third power transmission line according to the arrangement interval in a staggered manner according to the positions of the UHF sensors on the second power transmission line, wherein the staggered direction of the UHF sensors on the third power transmission line relative to the UHF sensors on the second power transmission line is the same as or opposite to the staggered direction of the UHF sensors on the second power transmission line relative to the UHF sensors on the first power transmission line.

[0062] S16: sequentially arranging UHF sensors on each power transmission line according to the method of S13 to S15.

[0063] S17: numbering all the UHF sensors and recording the position information of each sensor, wherein the position information comprises the number of the power transmission line to which the sensor belongs and the position coordinates of the sensor on the power transmission line.

[0064] It should be noted that the application uses UHF positioning method to locate the discharge part of high-voltage power transmission line, which has long detection distance, high sensitivity, can realize real-time online monitoring and can cover long line interval.

[0065] It should be noted that the symmetrical and uniform UHF sensor layout can improve the positioning accuracy of the discharge point on the high-voltage power transmission line.

[0066] It should be noted that the method for determining the arrangement interval of the UHF sensor is as follows: according to the measurable frequency of the UHF sensor and the attenuation characteristics of the electromagnetic wave in space transmission, the effective detection range of the UHF sensor is determined; at the same time, in order to meet the requirement of positioning accuracy on the spatial resolution of the sensor, the arrangement interval is set to be less than the effective detection distance, so as to ensure that any discharge point can be effectively captured by multiple sensors.

[0067] It should be noted that the electromagnetic signal with higher frequency attenuates faster, which limits the monitoring range of a single sensor, and the time difference positioning method needs to rely on the accurate time difference of the signal reaching different sensors, and smaller arrangement interval can improve the positioning accuracy and avoid monitoring blind area. According to the measurable frequency of the UHF sensor, the attenuation characteristics of the electromagnetic signal and the requirement of positioning accuracy, the arrangement interval of the UHF sensor is determined, which can take into account the monitoring sensitivity and positioning accuracy, and lay a foundation for subsequent accurate identification of the discharge part.

[0068] In the embodiment, the application sets the sensor layout interval and staggered mode scientifically, balances the monitoring sensitivity and positioning accuracy, avoids the blind area, and improves the coverage ability and monitoring efficiency of the long line section.

[0069] S2, discharge identification: real-time monitoring of the original signals captured by each UHF sensor, screening of effective signals according to the signal amplitude, judgment of whether it is a partial discharge signal based on the pulse characteristics of the effective signal, if yes, triggering a warning and entering step S3, if not, continuing to monitor the sensor signals.

[0070] As a preferred solution, referring to Figure 3 The specific analysis process of screening effective signals in step S2 is as follows: the amplitude of the original signal captured by the UHF sensor is obtained, and it is compared with the preset signal amplitude threshold value, if the amplitude of the original signal is greater than the signal amplitude threshold value, it is determined that the original signal is an effective signal, otherwise it is determined as a noise signal.

[0071] It should be noted that the threshold value of the signal amplitude is obtained by collecting and statistically analyzing the background electromagnetic signals of the high-voltage transmission line under normal non-discharge working conditions, selecting the upper limit of the statistical distribution of the background signal amplitude as the initial reference, and then calibrating and verifying it in combination with the amplitude characteristics of the typical partial discharge signals, so as to set a threshold value that can effectively distinguish between background noise and potential discharge signals.

[0072] It should be noted that the UHF electromagnetic signals generated by partial discharge are usually significantly higher in amplitude than the average level of electromagnetic noise introduced by the environment and system background during normal operation of the line. By setting a reasonable amplitude threshold value, the amplitude difference can be used for preliminary screening. Its role is to quickly eliminate most of the background noise in the massive monitoring data, greatly reducing the data volume and computational load of the subsequent signal processing and pattern recognition links, and providing a preprocessing basis for efficient and accurate identification of real partial discharge pulses.

[0073] As a preferred solution, the specific analysis process of judging whether it is a partial discharge signal in step S2 is as follows: based on the phase-resolved partial discharge spectrum of the effective signal, the pulse characteristics are extracted, including pulse phase distribution characteristics, pulse amplitude distribution characteristics, pulse repetition rate and pulse cross-correlation coefficient.

[0074] The extracted pulse characteristics are compared with the typical pulse characteristics of the pre-stored partial discharge signals in the database, and the degree of coincidence between the two is analyzed.

[0075] The coincidence degree is compared with the preset coincidence degree threshold value, if the coincidence degree is greater than or equal to the threshold value, it is determined that the effective signal is a partial discharge signal, otherwise it is determined as an interference signal.

[0076] It should be noted that the specific analysis process of analyzing the degree of coincidence between the effective signal pulse characteristics and the typical pulse characteristics of the partial discharge signal is as follows: D1: obtaining the pulse phase distribution characteristics of the effective signal, the pulse phase distribution characteristics including the number of pulse clusters, the average phase angle of the cluster, the phase span of the cluster, and the number ratio of positive and negative half-cycle pulses, comparing the pulse phase distribution characteristics of the effective signal with the typical pulse phase distribution characteristics of the partial discharge signal, obtaining the relative deviation of each sub-item of the pulse phase distribution characteristics of the effective signal from the corresponding sub-item of the typical pulse phase distribution characteristics of the partial discharge signal, combining the preset relationship function between the relative deviation of each sub-item of the pulse phase distribution characteristics and the coincidence factor, determining the coincidence factor of the pulse phase distribution characteristics of the effective signal and the typical pulse phase distribution characteristics of the partial discharge signal, and recording it as a first coincidence factor, the relationship function being a linear negative correlation function.

[0077] D2: obtaining the pulse amplitude distribution characteristics of the effective signal, the pulse amplitude distribution characteristics including skewness, kurtosis, and amplitude variation, comparing the pulse amplitude distribution characteristics of the effective signal with the typical pulse amplitude distribution characteristics of the partial discharge signal, analyzing the coincidence factor of the pulse amplitude distribution characteristics of the effective signal and the typical pulse amplitude distribution characteristics of the partial discharge signal, and recording it as a second coincidence factor.

[0078] D3: comparing the pulse repetition rate of the effective signal with the typical pulse repetition rate of the partial discharge signal to obtain the relative deviation, combining the preset mapping relationship between the relative deviation and the coincidence factor, determining the coincidence factor of the pulse repetition rate of the effective signal and the typical pulse repetition rate of the partial discharge signal, and recording it as a third coincidence factor.

[0079] D4: comparing the pulse cross-correlation coefficient of the effective signal with the typical pulse cross-correlation coefficient of the partial discharge signal to obtain the relative deviation, analyzing the coincidence factor of the pulse cross-correlation coefficient of the effective signal and the typical pulse cross-correlation coefficient of the partial discharge signal, and recording it as a fourth coincidence factor.

[0080] D5: accumulating the first coincidence factor, the second coincidence factor, the third coincidence factor, and the fourth coincidence factor to obtain the degree of coincidence between the pulse characteristics of the effective signal and the typical pulse characteristics of the partial discharge signal.

[0081] It should be noted that the coincidence threshold is determined by statistical analysis of the pulse characteristics of a large number of known types of partial discharge signals and typical interference signals. First, a training set containing multiple discharge modes and interference signal samples is constructed, the pulse characteristics in the PRPD pattern are extracted, and the coincidence with the standard discharge characteristics is calculated, thereby obtaining the coincidence distribution of the discharge samples and the interference samples, respectively. Then, according to the discrimination degree of the two types of samples, the critical value that can best distinguish partial discharge from interference signals is selected as the threshold, and in actual application, the verification set is used for calibration and optimization to ensure the accuracy and reliability of the judgment.

[0082] It should be noted that the partial discharge signal exhibits a pulse sequence with specific phase distribution, amplitude distribution, repetition rate and correlation in the PRPD pattern. These patterns are closely related to the type and severity of insulation defects, while general electromagnetic interference often does not have stable, correlated pulse aggregation characteristics. By comparing the coincidence of pulse characteristics and typical discharge patterns, the physical nature and statistical rules of discharge signals can be effectively utilized to distinguish them. Its role is to significantly improve the anti-interference ability and accuracy of discharge recognition, reduce false positives and false negatives, and provide reliable signal sources for subsequent positioning and diagnosis.

[0083] In this embodiment, the application adopts the combination of signal amplitude threshold screening and pulse feature matching to effectively distinguish partial discharge signals from background noise or lightning interference signals, greatly reducing the misjudgment rate and improving the anti-interference performance of the system.

[0084] S3, discharge positioning: preliminarily determining the discharge occurrence range according to the intensity of the partial discharge signal, constructing multiple triangular sensor arrays in the discharge occurrence range, analyzing the suspected discharge points corresponding to each sensor array using the time difference positioning method, determining the discharge site according to the analysis results of the suspected discharge points of each sensor array, and determining the discharge intensity of the discharge site.

[0085] As a preferred scheme, the specific process of analyzing the intensity of the partial discharge signal in step S3 is: obtaining the amplitude index and energy index of the partial discharge signal, the amplitude index including the peak amplitude and equivalent apparent discharge quantity, and the energy index including the pulse energy and average power.

[0086] The amplitude index and energy index are input into a preset signal intensity evaluation model to determine the intensity of the partial discharge signal, and the signal intensity evaluation model contains a quantitative mapping relationship between the amplitude index, the energy index and the signal intensity.

[0087] It should be noted that the signal strength evaluation model is established by: first, simulating or collecting historical data of UHF signal samples under different discharge types and intensities, extracting the amplitude and energy indicators of each sample and labeling the true discharge intensity; then using regression analysis, machine learning or other mathematical modeling methods to fit the quantitative mapping relationship between the amplitude indicator, energy indicator and discharge intensity, forming the evaluation model; finally, the model is tested and optimized using a validation dataset to ensure its accuracy and generalization ability.

[0088] It should be noted that the severity of partial discharge has a direct physical correlation with the amplitude of electromagnetic signals such as peak value, equivalent apparent discharge quantity and energy such as pulse energy, average power. The amplitude indicator reflects the instantaneous intensity of the discharge, and the energy indicator represents the continuous effect and overall level of the discharge. The combination of the two can comprehensively and objectively represent the actual intensity of the discharge. Its role is to provide quantitative and reliable intensity basis for subsequent determination of discharge range, assessment of defect severity and warning level, avoiding misjudgment that may be caused by a single indicator.

[0089] As a preferred solution, the specific analysis process for determining the discharge occurrence range in step S3 is: counting all UHF sensors that capture partial discharge signals and their corresponding partial discharge signal intensities.

[0090] Extract the numerical range of the partial discharge signal intensity corresponding to each intensity level pre-stored in the database.

[0091] The areas covered by UHF sensors with partial discharge signal intensities in the high, medium and low intensity level numerical ranges are sequentially recorded as the discharge core area, the transition area and the edge area.

[0092] Integrate the discharge core area, transition area and edge area to determine the final discharge occurrence range.

[0093] It should be noted that the numerical range of the partial discharge signal intensity corresponding to each intensity level is determined by statistical analysis of a large number of historical discharge case data. The specific process includes: collecting partial discharge signal samples under different working conditions and different defect types, measuring their signal intensity indicators such as peak amplitude, pulse energy, etc., and performing clustering analysis or percentile division according to the actual discharge severity or expert experience, thereby dividing the signal intensity range into numerical ranges corresponding to high, medium and low intensity levels, and continuously optimizing and calibrating in application according to field feedback.

[0094] It should be noted that the strength of the partial discharge signal is closely related to the propagation distance, and the closer the sensor is to the discharge point, the higher the signal strength received. Therefore, the core area and the impact range of the discharge activity can be deduced according to the spatial distribution characteristics of the signal strength. By dividing the sensors into core area, transition area and edge area according to the signal strength, the spatial range of the discharge occurrence can be preliminarily defined. The role is to narrow the search area of subsequent accurate positioning, significantly improve the calculation efficiency and positioning accuracy of the time difference positioning algorithm, and provide spatial constraints for quickly and accurately finding the discharge site.

[0095] As a preferred solution, the specific process of analyzing the suspected discharge point corresponding to each sensor array in step S3 is: extracting the pre-stored spatial model of multiple parallel high-voltage transmission lines in the database, intercepting the high-voltage transmission line spatial model corresponding to the discharge occurrence range, and marking the positions of all UHF sensors in the range.

[0096] Three UHF sensors that are not collinear in space are defined as a triangular sensor array.

[0097] All UHF sensors in the discharge occurrence range are combined in threes to construct multiple triangular sensor arrays.

[0098] It should be noted that the specific method of combining all UHF sensors in the discharge occurrence range in threes to construct multiple triangular sensor arrays is: assuming that there are UHF sensors in the discharge occurrence range, all possible and different three-combinations are systematically and without omission selected from all UHF sensors in the discharge occurrence range, and this process is equivalent to calculating the combination number , that is, all ways of taking 3 from N different elements, and each way corresponds to a potential triangular sensor array.

[0099] For each selected three-combination, check whether its spatial position satisfies the geometric condition of not being collinear. This check can be based on the three-dimensional coordinates of the sensors in the pre-stored high-voltage transmission line spatial model.

[0100] If the three points are not collinear, the combination is defined and constructed as a triangular sensor array, and the triangular array takes the spatial positions of the three sensors as vertices to form a unique spatial plane.

[0101] Finally, all combinations that pass the check are formally defined as valid "triangular sensor arrays".

[0102] For each triangular sensor array, the time difference of the same partial discharge signal captured by each two sensors in the array is obtained, and the time difference positioning method is used to calculate and determine one or more suspected discharge points corresponding to the triangular sensor array, combined with the electromagnetic wave propagation speed.

[0103] It should be noted that the spatial model of the high-voltage transmission line is constructed based on real-world images collected by UAV inspections and is dynamically updated.

[0104] As a preferred embodiment, the specific process of determining the suspected discharge point corresponding to the triangular sensor array using the time difference positioning method is as follows: The three sensors within the triangular sensor array are respectively denoted as... And obtain the time when each sensor captures the same partial discharge signal.

[0105] calculate and Time difference of signal acquisition Combined with the speed of electromagnetic wave propagation Through formula Calculate the discharge point To the sensor and Distance difference ,by , Draw a hyperbola that satisfies the distance difference around the focus, and denote it as the first hyperbola.

[0106] Similarly, based on , Time difference of signal acquisition and , Time difference of signal acquisition Draw the second and third hyperbolas respectively.

[0107] The intersection of the three hyperbolas is determined as the suspected discharge point corresponding to the triangular sensor array. There can be one or more suspected discharge points, and the spatial coordinates of the suspected discharge points are recorded.

[0108] It should be noted that the propagation speed of the electromagnetic wave was determined experimentally in advance.

[0109] As a preferred embodiment, the specific process of determining the discharge location and analyzing its discharge intensity in step S3 is as follows: T1: In the high-voltage transmission line spatial model of the section corresponding to the discharge occurrence range, mark all suspected discharge points corresponding to each triangular sensor array, and remove abnormal points that are obviously far away from the transmission line according to preset rules to obtain the optimized spatial distribution of suspected discharge points.

[0110] T2: If the suspected discharge points converge at a single location in space, then that point is directly identified as the discharge site; otherwise, proceed to T3.

[0111] T3: Calculate the spatial distance between each suspected discharge point, if the distance between any two points is less than the set spatial distance threshold, then determine that the two belong to the same discharge point group.

[0112] Count the number of all discharge point groups.

[0113] If there is only one discharge point group, determine the geometric center of the point group as the discharge site, otherwise go to T4.

[0114] T4: Count the number of suspected discharge points contained in each discharge point group, and calculate the average number of points contained in all point groups.

[0115] If the number of points in a discharge point group is higher than the average and the excess reaches a set threshold, define the point group as the main discharge point group.

[0116] Count the number of main discharge point groups: if there is only one main point group, determine the center point as the discharge site, if there are two main point groups, determine the midpoint of the line connecting the two main point group center points as the discharge site, if there are more than two main point groups, go to T5.

[0117] T5: Connect the center points of each main discharge point group in turn to form a polygonal region, and determine the geometric center of the polygonal region as the discharge site.

[0118] T6: Determine the highest intensity in the partial discharge signal captured by all UHF sensors in the discharge occurrence range as the discharge intensity of the discharge site.

[0119] It should be noted that the specific process of removing abnormal points obviously far away from the power transmission line is: obtaining the distance between the suspected discharge point and the power transmission line and comparing the distance with the set distance range, if the distance exceeds the range, it is determined as an abnormal point and is removed.

[0120] In this embodiment, the present application constructs multiple triangular sensor arrays by arranging UHF sensors on multiple power transmission lines in an equal interval staggered manner, uses time difference positioning method for multi-dimensional space positioning, effectively avoids single path interference, and significantly improves the positioning accuracy and result reliability of discharge points.

[0121] S4, severity assessment: collect visible light images of the discharge site by the unmanned aerial vehicle, extract physical defect information and analyze the defect degree, evaluate the discharge severity combining the defect degree of the discharge site and the discharge intensity, and generate a detection report.

[0122] As a preferred scheme, the specific analysis process of step S4 is: collecting visible light images of the area where the discharge site is located by the unmanned aerial vehicle, and extracting physical defect information from the images based on image processing technology, the physical defect information includes deformation amount and damage area.

[0123] According to the preset relationship function between the deformation amount and the defect degree, the defect degree of the discharge position is determined.

[0124] The defect degree and the discharge intensity are weighted and fused for analysis, and a quantitative evaluation result of the discharge severity is obtained.

[0125] It should be noted that the physical defects of the discharge position are recognized and quantified by means of the pre-stored sample images of the physical defects caused by the historical discharge of the high-voltage transmission line in the database.

[0126] It should be noted that the weights of the defect degree and the discharge intensity can be preset according to industry experience or determined through limited test data; for example, historical data of the discharge defect types of the high-voltage transmission line and the occurrence frequency thereof are collected first, then the correlation coefficients of the influence of the defect degree and the discharge intensity on the overall discharge severity are calculated, the contribution degrees of the indexes are determined by using regression analysis or analytic hierarchy process, finally the contribution degrees are converted into the weights of the defect degree and the discharge intensity through normalization processing, and the sum of the weights is 1.

[0127] It should be noted that the detection report is generated according to the position of the discharge position and the discharge severity.

[0128] In the embodiment, the discharge intensity during discharge and the physical defect information after discharge are comprehensively analyzed, and a quantitative evaluation result of the discharge severity is generated through weighted and fused analysis, so that more comprehensive and objective basis is provided for operation and maintenance decision-making.

[0129] The above formulas are all dimensionless values, and the formulas are obtained by software simulation of a large amount of data to obtain a formula of the nearest real situation, and the preset parameters in the formula are set by a person skilled in the art according to the actual situation.

[0130] The above embodiments can be realized wholly or partially by software, hardware, firmware or any combination thereof. When realized by software, the above embodiments can be realized in the form of a computer program product wholly or partially.

[0131] Those skilled in the art can realize that the modules and algorithm steps of the examples described in combination with the embodiments disclosed herein can be realized by electronic hardware or a combination of computer software and electronic hardware. Whether the functions are realized by hardware or software depends on the specific application and design constraints of the technical solutions. A person skilled in the art can use different methods to realize the described functions for each specific application, but such implementation should not be considered beyond the scope of the present application.

[0132] In addition, each function module in each embodiment of the present application can be integrated in one processing module, or each module can be physically present alone, or two or more modules can be integrated in one module.

[0133] The above is merely specific embodiments of the present application, but the protection scope of the present application is not limited thereto, any person skilled in the art can easily think of changes or replacements within the technical range disclosed by the present application, which should be covered in the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

[0134] Finally, the above is merely preferred embodiments of the present application, and is not used to limit the present application, any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be covered in the protection scope of the present application.

Claims

1. A method for intelligent detection of discharge sites on high voltage power lines, characterized in that, The method comprises the following steps: S1, sensor arrangement: uniformly arranging a plurality of UHF sensors on a plurality of high-voltage transmission lines arranged side by side in an equal-interval staggered manner, numbering and recording the positions of the UHF sensors; S2, discharge identification: monitoring the original signals captured by each UHF sensor in real time, screening out effective signals according to the signal amplitudes, judging whether the effective signals are local discharge signals based on the pulse characteristics of the effective signals, if yes, triggering a warning and entering step S3, if not, continuing to monitor the sensor signals; S3, discharge positioning: preliminarily determining the discharge occurrence range according to the strength of the local discharge signals, constructing a plurality of triangular sensor arrays in the discharge occurrence range, analyzing the suspected discharge points corresponding to each sensor array by using the time difference positioning method, determining the discharge site according to the analysis results of the suspected discharge points of each sensor array, and determining the discharge strength of the discharge site; S4, severity evaluation: collecting visible light images of the discharge site by using a UAV, extracting physical defect information and analyzing the defect degree, combining the defect degree of the discharge site and the discharge strength to evaluate the discharge severity, and generating a detection report.

2. The method of claim 1, wherein the method comprises: The specific analysis process of step S1 is as follows: S11: according to the measurable frequency of the UHF sensor, the electromagnetic signal attenuation characteristics and the positioning accuracy requirement, the interval between the two adjacent UHF sensors is determined as the arrangement interval; S12: each transmission line is sorted in the order from one side to the other side; S13: a plurality of UHF sensors are uniformly arranged on the first transmission line at the arrangement interval; S14: according to the position of the UHF sensor on the first transmission line, a plurality of UHF sensors are uniformly arranged on the second transmission line at the arrangement interval in a staggered manner; S15: according to the position of the UHF sensor on the second transmission line, a plurality of UHF sensors are uniformly arranged on the third transmission line at the arrangement interval in a staggered manner, wherein the staggered direction of the UHF sensors on the third transmission line relative to the UHF sensors on the second transmission line is the same as or opposite to the staggered direction of the UHF sensors on the second transmission line relative to the UHF sensors on the first transmission line; S16: according to the method described in S13 to S15, the UHF sensors are arranged on each transmission line in turn; S17: all UHF sensors are numbered, and the position information of each sensor is recorded, the position information including the transmission line number and the position coordinates of the UHF sensor on the transmission line.

3. The method of claim 1, wherein the method further comprises: The specific analysis process of screening effective signals in step S2 is as follows: The amplitude of the original signal captured by the UHF sensor is obtained, and compared with the preset signal amplitude threshold value, if the amplitude of the original signal is greater than the signal amplitude threshold value, the original signal is determined as an effective signal, otherwise it is determined as a noise signal.

4. The method of claim 1, wherein the method further comprises: The specific analysis process of judging whether it is a local discharge signal in step S2 is as follows: Based on the phase-resolved partial discharge spectrum of the effective signal, the pulse characteristics are extracted, The pulse characteristics include pulse phase distribution characteristics, pulse amplitude distribution characteristics, pulse repetition rate and pulse cross-correlation coefficient; The extracted pulse feature is compared with the typical pulse feature of the pre-stored partial discharge signal in the database, and the coincidence degree between the two is analyzed; The coincidence degree is compared with a preset coincidence degree threshold value, and if the coincidence degree is greater than or equal to the threshold value, the effective signal is determined to be a partial discharge signal, otherwise it is determined to be an interference signal.

5. The method of claim 1, wherein the method further comprises: The specific process of analyzing the partial discharge signal strength in step S3 is: Obtain the amplitude index and energy index of the partial discharge signal, the amplitude index including the peak amplitude and equivalent apparent discharge quantity, and the energy index including the pulse energy and average power; The amplitude index and energy index are input into a preset signal strength evaluation model to determine the strength of the partial discharge signal, and the signal strength evaluation model contains a quantitative mapping relationship between the amplitude index, energy index and signal strength.

6. The method of claim 1, wherein the method further comprises: The specific analysis process of determining the discharge occurrence range in step S3 is: Statistical all UHF sensors that capture partial discharge signals and their corresponding partial discharge signal strengths; Extract the numerical interval of the partial discharge signal strength corresponding to each intensity level pre-stored in the database; The areas covered by the UHF sensors whose partial discharge signal strengths are located in the numerical interval of the high intensity level, the medium intensity level and the low intensity level are sequentially recorded as the discharge core area, the transition area and the edge area; Integrate the discharge core area, the transition area and the edge area to determine the final discharge occurrence range.

7. The method of claim 1, wherein the method further comprises: determining a location of the discharge site on the high voltage transmission line. The specific process of analyzing the suspected discharge point corresponding to each sensor array in step S3 is: Extract the spatial model of multiple parallel high-voltage transmission lines pre-stored in the database, intercept the high-voltage transmission line spatial model corresponding to the section of the discharge occurrence range, and mark the positions of all UHF sensors in the range; Three UHF sensors that are not collinear in space are defined as a triangular sensor array; All UHF sensors in the discharge occurrence range are combined in threes to construct multiple triangular sensor arrays: there are UHF sensors in the discharge occurrence range, the combination number , that is, all ways of taking 3 from N different elements, each way corresponds to a potential triangular sensor array, the spatial positions of the selected three UHF sensors are checked to see if they satisfy the geometric condition of not being collinear, if not, the three UHF sensors are defined and constructed into a triangular sensor array; For each triangular sensor array, obtain the time difference of the same partial discharge signal captured by each two sensors in the array, combine the electromagnetic wave propagation speed, and use the time difference positioning method to calculate and determine one or more suspected discharge points corresponding to the triangular sensor array.

8. The method of claim 7, wherein the method further comprises: The specific process of using the time difference positioning method to determine the suspected discharge point corresponding to the triangular sensor array is: The three sensors within the triangular sensor array are denoted as and the time at which each sensor captures the same partial discharge signal is obtained; Computing and the time difference of the captured signals in combination with the electromagnetic wave propagation speed by the formula to calculate the discharge point to the distance difference to the distance difference to , draw a hyperbola that satisfies this distance difference with the focus, denoted as the first hyperbola; Similarly, based on , time difference of the captured signals and , time difference of the captured signals , a second hyperbola and a third hyperbola are plotted, respectively; Determine the intersection of the three hyperbolas as the suspected discharge point corresponding to the triangular sensor array, which can be one or more, and record the spatial coordinates of the suspected discharge point.

9. The method of claim 1, wherein the method further comprises: determining a location of the discharge site on the high voltage transmission line. The specific process of determining the discharge site and analyzing the discharge strength in step S3 is: T1: In the high-voltage transmission line spatial model corresponding to the section of the discharge occurrence range, mark all suspected discharge points corresponding to each triangular sensor array, and remove abnormal points obviously far from the transmission line according to a preset rule to obtain an optimized suspected discharge point spatial distribution; T2: If the suspected discharge points converge at a single position in space, the point is directly determined as the discharge site, otherwise T3 is entered; T3: Calculate the spatial distance between each suspected discharge point, and if the distance between any two points is less than a set spatial distance threshold, it is determined that they belong to the same discharge point group; Statistical all discharge point groups; If there is only one discharge point group, the geometric center of the point group is determined as the discharge site, otherwise, enter T4; T4: Count the number of suspected discharge points in each discharge point group, and calculate the average number of points contained in all point groups; If the number of points in a discharge point group is higher than the average and the excess reaches a set threshold, the point group is defined as the main discharge point group; Count the number of main discharge point groups: If there is only one main point group, the center point is determined as the discharge site, if there are two main point groups, the midpoint of the line connecting the two main point group center points is determined as the discharge site, if there are more than two main point groups, enter T5; T5: Connect the center points of each main discharge point group in turn to form a polygonal region, and determine the geometric center of the polygonal region as the discharge site; T6: Determine the highest intensity in the partial discharge signal captured by all UHF sensors in the discharge occurrence range as the discharge intensity of the discharge site.

10. The method of claim 1, wherein the method further comprises: The specific analysis process of step S4 is: Collect visible light images of the area where the discharge site is located by the unmanned aerial vehicle, and extract physical defect information from the images based on image processing technology, the physical defect information including deformation and damage area; According to the preset relationship function between deformation and damage area and defect degree, the defect degree of the discharge site is determined; Weighted fusion analysis of the defect degree and discharge intensity is performed to obtain the quantitative evaluation result of the discharge severity.

Images