CN113552444A - Online setting method and device for leakage current characteristic threshold - Google Patents

Online setting method and device for leakage current characteristic threshold Download PDF

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Publication number
CN113552444A
CN113552444A CN202110654685.1A CN202110654685A CN113552444A CN 113552444 A CN113552444 A CN 113552444A CN 202110654685 A CN202110654685 A CN 202110654685A CN 113552444 A CN113552444 A CN 113552444A
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leakage current
sample data
sample
probability
variance
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张瑜
宋晓辉
盛万兴
孟晓丽
李建芳
高菲
李雅洁
赵珊珊
徐冬杰
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State Grid Corp of China SGCC
China Electric Power Research Institute Co Ltd CEPRI
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China Electric Power Research Institute Co Ltd CEPRI
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/08—Locating faults in cables, transmission lines, or networks
    • G01R31/081—Locating faults in cables, transmission lines, or networks according to type of conductors
    • G01R31/086—Locating faults in cables, transmission lines, or networks according to type of conductors in power transmission or distribution networks, i.e. with interconnected conductors
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/50—Testing of electric apparatus, lines, cables or components for short-circuits, continuity, leakage current or incorrect line connections
    • G01R31/52—Testing for short-circuits, leakage current or ground faults
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R35/00—Testing or calibrating of apparatus covered by the other groups of this subclass
    • G01R35/005—Calibrating; Standards or reference devices, e.g. voltage or resistance standards, "golden" references

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  • Testing Of Short-Circuits, Discontinuities, Leakage, Or Incorrect Line Connections (AREA)

Abstract

The invention relates to the technical field of analysis of running states of power distribution network equipment, and particularly provides an online setting method and device of a leakage current characteristic threshold, aiming at solving the technical problem that a preset leakage current threshold cannot change along with environmental changes. The method comprises the following steps: dividing the gray scale of the sample data of the amplitude value of the leakage current, and calculating the sample probability corresponding to each gray scale; selecting a plurality of threshold values, and dividing leakage current amplitude sample data into two groups respectively based on the threshold values; calculating the variance between the two groups based on the sample probability corresponding to each gray level; taking two groups of corresponding threshold values with the largest variance as leakage current characteristic threshold values of the power distribution network cable line; the scheme provides judgment basis and measurement standard for realizing online insulation state monitoring analysis and judgment in the actual operation of the power distribution network equipment.

Description

Online setting method and device for leakage current characteristic threshold
Technical Field
The invention relates to the field of analysis of running states of power distribution network equipment, in particular to a method and a device for online setting of a leakage current characteristic threshold.
Background
The leakage current is one of important characteristics reflecting the insulation condition of a cable line of the power distribution network, and the leakage current characteristic threshold is a quantitative basis for judging the insulation condition. However, the setting of the leakage current characteristic threshold value at present usually depends on test detection or experience of an operator to perform off-line setting and setting.
In the actual operation stage, the leakage current can change along with the difference of the actual operation condition, the operation environment and the load level of the power grid, and if the preset leakage current threshold value cannot change along with the change of the leakage current threshold value, the misjudgment of the insulation state of the cable is certainly caused. Therefore, an adaptive online setting method of the leakage current threshold is urgently needed to be sought, and judgment basis and measurement standard are provided for more accurately judging the insulation state of the cable.
Disclosure of Invention
In order to overcome the defects, the invention is provided to provide an online setting method and an online setting device for the leakage current characteristic threshold, which solve or at least partially solve the technical problem that the preset leakage current threshold cannot change along with environmental changes.
In a first aspect, an online setting method for a leakage current characteristic threshold is provided, where the online setting method for the leakage current characteristic threshold includes:
dividing the gray scale of the sample data of the amplitude value of the leakage current, and calculating the sample probability corresponding to each gray scale;
selecting a plurality of threshold values, and dividing leakage current amplitude sample data into two groups respectively based on the threshold values;
calculating the variance between the two groups based on the sample probability corresponding to each gray level;
and taking the two groups of corresponding threshold values with the largest variance as the leakage current characteristic threshold values of the cable lines of the power distribution network.
Preferably, the calculation formula of the sample probability corresponding to the gray scale is as follows:
Figure BDA0003113318180000011
in the above formula, PjSample probability, n, for the jth gray leveljThe number of samples corresponding to the jth gray level, N is the total number of samples in the sample data of the leakage current amplitude value, j belongs to [1, L ]]And L is the total number of preset gray levels.
Preferably, the number of samples corresponding to the jth gray scale is [ (j-1) d ] in the leakage current amplitude sample datax,jdx]Number of samples within a range, wherein dxThe group width of the leakage current amplitude sample data.
Further, the calculation formula of the group width of the leakage current amplitude sample data is as follows:
Figure BDA0003113318180000021
in the above formula, dxFor the group width, X, of the sample data of the magnitude of the leakage currentmaxIs the maximum value, X, in the sample data of the leakage current amplitudeminAnd L is the minimum value in the sample data of the leakage current amplitude, and is the total number of preset gray levels.
Preferably, the dividing the sample data of the magnitude of the leakage current into two groups based on the respective thresholds includes:
setting the leakage current amplitude sample data at [0, kdx]Sample partitioning into set C within range0Sampling the leakage current amplitude at [ (k +1) d%x,Ldx]Sample partitioning into set C within range1Wherein k is a threshold coefficient, k belongs to [1, L ]]，dxIs the group width of sample data of leakage current amplitude, L is the total number of preset gray levels, kdxIs the selected threshold.
Further, the calculating the variance between the two groups based on the sample probability corresponding to each gray scale includes:
calculating a set C based on sample probability corresponding to each gray level0And set C1Mean and probability of;
based on set C0And set C1Set of mean and probability calculations C0And set C1The variance between.
Further, the set C0The calculation formula of the mean value of (a) is as follows:
Figure BDA0003113318180000022
the set C0The probability of (a) is calculated as follows:
Figure BDA0003113318180000023
the set C1The calculation formula of the mean value of (a) is as follows:
Figure BDA0003113318180000024
the set C1The probability of (a) is calculated as follows:
Figure BDA0003113318180000025
in the above formula,. mu.0Is set C0Mean value of pjSample probability, p, for the jth gray level0Is set C0Probability of (n)jThe number of samples corresponding to the jth gray level, N is the total number of samples in the sample data of the leakage current amplitude value, mu1Is set C1Mean value of p1Is set C1L is the total number of preset gray levels.
Further, the set C0And set C1The variance between is calculated as follows:
σ2＝P0(μ0-μ)2+P1(μ1-μ)2
in the above formula, σ2Is set C0And set C1The variance between the values, mu, P, is the mean of all the leakage current amplitude sample data0μ0+P1μ1。
In a second aspect, an online setting device for a leakage current characteristic threshold is provided, and the online setting device for the leakage current characteristic threshold includes:
the first calculation module is used for dividing the gray level of the sample data of the amplitude value of the leakage current and calculating the sample probability corresponding to each gray level;
the grouping module is used for selecting a plurality of thresholds and respectively grouping the leakage current amplitude sample data into two groups based on the thresholds;
the second calculation module is used for calculating the variance between the two groups based on the sample probability corresponding to each gray level;
and the determining module is used for taking the two groups of corresponding threshold values with the largest variance as the characteristic threshold values of the leakage current of the cable line of the power distribution network.
One or more technical schemes of the invention at least have one or more of the following beneficial effects:
the invention relates to the technical field of analysis of running states of power distribution network equipment, and particularly provides an online setting method and device of a leakage current characteristic threshold, aiming at solving the technical problem that a preset leakage current threshold cannot change along with environmental changes. The method comprises the following steps: dividing the gray scale of the sample data of the amplitude value of the leakage current, and calculating the sample probability corresponding to each gray scale; selecting a plurality of threshold values, and dividing leakage current amplitude sample data into two groups respectively based on the threshold values; calculating the variance between the two groups based on the sample probability corresponding to each gray level; taking two groups of corresponding threshold values with the largest variance as leakage current characteristic threshold values of the power distribution network cable line; the scheme can adaptively determine the optimal amplitude threshold according to the characteristics of the original sample data of the leakage current so as to adapt to the situation that when the sample data of the leakage current changes, the adoption of the same threshold can cause misjudgment on the abnormal out-of-limit condition of the leakage current, and finally realize the online setting of the threshold of the leakage current. Furthermore, the threshold interval obtained by calculating leakage current real-time data is more accurate, and more accurate criterion conditions are provided for identifying the insulation state of the cable line of the power distribution network.
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FIG. 1 is a flow chart illustrating the main steps of an online setting method for leakage current characteristic threshold according to an embodiment of the present invention;
fig. 2 is a main structural block diagram of an online setting device for leakage current characteristic threshold according to an embodiment of the present invention.
Detailed Description
The following describes embodiments of the present invention in further detail with reference to the accompanying drawings.
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The invention discloses an online setting method of a leakage current characteristic threshold, which aims to obtain real-time leakage current amplitude original sample data recorded in a period of time, and based on the characteristics of large range and dispersed distribution of leakage current abnormal values compared with normal values, the optimal threshold of the leakage current amplitude is obtained by adopting the maximum inter-class variance method to calculate, so that the variance between the normal value and the abnormal values of the leakage current is maximum, and finally, the accurate judgment of the abnormal out-of-limit condition of the leakage current is realized. The method can adaptively determine the optimal amplitude threshold according to the characteristics of the original sample data of the leakage current so as to adapt to the situation that when the sample data of the leakage current changes, the adoption of the same threshold can cause misjudgment on the abnormal out-of-limit condition of the leakage current, and finally realize the online setting of the threshold of the leakage current.
Referring to fig. 1, fig. 1 is a flow chart illustrating main steps of an online setting method for a leakage current characteristic threshold according to an embodiment of the invention. As shown in fig. 1, the online setting method for the leakage current characteristic threshold in the embodiment of the present invention mainly includes the following steps:
step S101: dividing the gray scale of the sample data of the amplitude value of the leakage current, and calculating the sample probability corresponding to each gray scale;
step S102: selecting a plurality of threshold values, and dividing leakage current amplitude sample data into two groups respectively based on the threshold values;
step S103: calculating the variance between the two groups based on the sample probability corresponding to each gray level;
step S104: and taking the two groups of corresponding threshold values with the largest variance as the leakage current characteristic threshold values of the cable lines of the power distribution network.
In this embodiment, the calculation formula of the sample probability corresponding to the gray scale is as follows:
Figure BDA0003113318180000041
in the above formula, PjSample probability, n, for the jth gray leveljThe number of samples corresponding to the jth gray level, N is the total number of samples in the sample data of the leakage current amplitude value, j belongs to [1, L ]]And L is the total number of preset gray levels.
In this embodiment, the jth gray scaleThe number of samples corresponding to the grade is [ (j-1) d ] in the leakage current amplitude sample datax,jdx]Number of samples within a range, wherein dxThe group width of the leakage current amplitude sample data.
In one embodiment, the group width of the leakage current magnitude sample data is calculated as follows:
Figure BDA0003113318180000042
in the above formula, dxFor the group width, X, of the sample data of the magnitude of the leakage currentmaxIs the maximum value, X, in the sample data of the leakage current amplitudeminAnd L is the minimum value in the sample data of the leakage current amplitude, and is the total number of preset gray levels.
In this embodiment, the dividing the sample data of the magnitude of the leakage current into two groups based on the respective thresholds includes:
setting the leakage current amplitude sample data at [0, kdx]Sample partitioning into set C within range0Sampling the leakage current amplitude at [ (k +1) d%x,Ldx]Sample partitioning into set C within range1Wherein k is a threshold coefficient, k belongs to [1, L ]]，dxIs the group width of sample data of leakage current amplitude, L is the total number of preset gray levels, kdxIs the selected threshold.
In one embodiment, the calculating the variance between the two groups based on the sample probability corresponding to each gray scale includes:
calculating a set C based on sample probability corresponding to each gray level0And set C1Mean and probability of;
based on set C0And set C1Set of mean and probability calculations C0And set C1The variance between.
Wherein the set C0The calculation formula of the mean value of (a) is as follows:
Figure BDA0003113318180000051
the set C0The probability of (a) is calculated as follows:
Figure BDA0003113318180000052
the set C1The calculation formula of the mean value of (a) is as follows:
Figure BDA0003113318180000053
the set C1The probability of (a) is calculated as follows:
Figure BDA0003113318180000054
in the above formula,. mu.0Is set C0Mean value of pjSample probability, p, for the jth gray level0Is set C0Probability of (n)jThe number of samples corresponding to the jth gray level, N is the total number of samples in the sample data of the leakage current amplitude value, mu1Is set C1Mean value of p1Is set C1L is the total number of preset gray levels.
The set C0And set C1The variance between is calculated as follows:
σ2＝P0(μ0-μ)2+P1(μ1-μ)2
in the above formula, σ2Is set C0And set C1The variance between the values, mu, P, is the mean of all the leakage current amplitude sample data0μ0+P1μ1。
Further, based on the above scheme, the present invention provides an optimal implementation manner, which is as follows:
(1) obtaining a time interval noteRecorded real-time leakage current amplitude original sample data { X }iI is 1,2, … N, and the maximum value is XmaxMinimum value of Xmin；
(2) Arranging original sample data of the leakage current amplitude in a period of time from large to small, and dividing L gray levels according to different leakage current amplitudes, wherein the gray levels are represented by gray values j of 1,2 and … L;
(3) order to
Figure BDA0003113318180000061
Statistics fall on [ (j-1) dx,jdx]Number of leakage current samples n within rangej，N＝n1+n2+…nL；
(4) Calculating the probability of occurrence of the gray value j as
Figure BDA0003113318180000062
(5) Set a threshold kdxThe original sample sequences are divided into two categories: c0Represents a range of [0, kd ]x]A value of (1); c1The characterization range is [ (k +1) dx,Ldx]A value of (1);
(6) calculating a new sample C0The mean and probability of (d) are respectively:
Figure BDA0003113318180000063
Figure BDA0003113318180000064
(7) calculating a new sample C1The mean and probability of (d) are respectively:
Figure BDA0003113318180000065
Figure BDA0003113318180000066
(8) calculate the mean of all samples μ ═ P0μ0+P1μ1；
(9) Calculating the between-class variance sigma of two new samples2＝P0(μ0-μ)2+P1(μ1-μ)2；
(10) Calculating an optimal threshold kdx *To maximize the inter-class variance
Figure BDA0003113318180000067
Based on the same technical scheme, the invention provides an online setting device for a leakage current characteristic threshold, as shown in fig. 2, the online setting device for the leakage current characteristic threshold comprises:
the first calculation module is used for dividing the gray level of the sample data of the amplitude value of the leakage current and calculating the sample probability corresponding to each gray level;
the grouping module is used for selecting a plurality of thresholds and respectively grouping the leakage current amplitude sample data into two groups based on the thresholds;
the second calculation module is used for calculating the variance between the two groups based on the sample probability corresponding to each gray level;
and the determining module is used for taking the two groups of corresponding threshold values with the largest variance as the characteristic threshold values of the leakage current of the cable line of the power distribution network.
Preferably, the calculation formula of the sample probability corresponding to the gray scale is as follows:
Figure BDA0003113318180000071
in the above formula, PjSample probability, n, for the jth gray leveljThe number of samples corresponding to the jth gray level, N is the total number of samples in the sample data of the leakage current amplitude value, j belongs to [1, L ]]And L is the total number of preset gray levels.
Preferably, the j-th gray scale corresponds toThe number of samples is [ (j-1) d ] in the leakage current amplitude sample datax,jdx]Number of samples within a range, wherein dxThe group width of the leakage current amplitude sample data.
Further, the calculation formula of the group width of the leakage current amplitude sample data is as follows:
Figure BDA0003113318180000072
in the above formula, dxFor the group width, X, of the sample data of the magnitude of the leakage currentmaxIs the maximum value, X, in the sample data of the leakage current amplitudeminAnd L is the minimum value in the sample data of the leakage current amplitude, and is the total number of preset gray levels.
Preferably, the dividing the sample data of the magnitude of the leakage current into two groups based on the respective thresholds includes:
setting the leakage current amplitude sample data at [0, kdx]Sample partitioning into set C within range0Sampling the leakage current amplitude at [ (k +1) d%x,Ldx]Sample partitioning into set C within range1Wherein k is a threshold coefficient, k belongs to [1, L ]]，dxIs the group width of sample data of leakage current amplitude, L is the total number of preset gray levels, kdxIs the selected threshold.
Further, the calculating the variance between the two groups based on the sample probability corresponding to each gray scale includes:
calculating a set C based on sample probability corresponding to each gray level0And set C1Mean and probability of;
based on set C0And set C1Set of mean and probability calculations C0And set C1The variance between.
Further, the set C0The calculation formula of the mean value of (a) is as follows:
Figure BDA0003113318180000081
the set C0The probability of (a) is calculated as follows:
Figure BDA0003113318180000082
the set C1The calculation formula of the mean value of (a) is as follows:
Figure BDA0003113318180000083
the set C1The probability of (a) is calculated as follows:
Figure BDA0003113318180000084
in the above formula,. mu.0Is set C0Mean value of pjSample probability, p, for the jth gray level0Is set C0Probability of (n)jThe number of samples corresponding to the jth gray level, N is the total number of samples in the sample data of the leakage current amplitude value, mu1Is set C1Mean value of p1Is set C1L is the total number of preset gray levels.
Further, the set C0And set C1The variance between is calculated as follows:
σ2＝P0(μ0-μ)2+P1(μ1-μ)2
in the above formula, σ2Is set C0And set C1The variance between the values, mu, P, is the mean of all the leakage current amplitude sample data0μ0+P1μ1。
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solutions of the present invention and not for limiting the same, and although the present invention is described in detail with reference to the above embodiments, those of ordinary skill in the art should understand that: modifications and equivalents may be made to the embodiments of the invention without departing from the spirit and scope of the invention, which is to be covered by the claims.

Claims (9)

1. An online setting method for a leakage current characteristic threshold is characterized by comprising the following steps:
dividing the gray scale of the sample data of the amplitude value of the leakage current, and calculating the sample probability corresponding to each gray scale;
selecting a plurality of threshold values, and dividing leakage current amplitude sample data into two groups respectively based on the threshold values;
calculating the variance between the two groups based on the sample probability corresponding to each gray level;
and taking the two groups of corresponding threshold values with the largest variance as the leakage current characteristic threshold values of the cable lines of the power distribution network.
2. The method of claim 1, wherein the sample probability for the gray scale is calculated as follows:
Figure FDA0003113318170000011
in the above formula, PjSample probability, n, for the jth gray leveljThe number of samples corresponding to the jth gray level, N is the total number of samples in the sample data of the leakage current amplitude value, j belongs to [1, L ]]And L is the total number of preset gray levels.
3. The method of claim 1, wherein the number of samples corresponding to the jth gray scale level is [ (j-1) d ] in the leakage current amplitude sample datax,jdx]Number of samples within a range, wherein dxThe group width of the leakage current amplitude sample data.
4. The method of claim 3, wherein the group width of the leakage current magnitude sample data is calculated as follows:
Figure FDA0003113318170000012
in the above formula, dxFor the group width, X, of the sample data of the magnitude of the leakage currentmaxIs the maximum value, X, in the sample data of the leakage current amplitudeminAnd L is the minimum value in the sample data of the leakage current amplitude, and is the total number of preset gray levels.
5. The method of claim 1, wherein said separately grouping leakage current magnitude sample data into two groups based on respective thresholds comprises:
setting the leakage current amplitude sample data at [0, kdx]Sample partitioning into set C within range0Sampling the leakage current amplitude at [ (k +1) d%x,Ldx]Sample partitioning into set C within range1Wherein k is a threshold coefficient, k belongs to [1, L ]]，dxIs the group width of sample data of leakage current amplitude, L is the total number of preset gray levels, kdxIs the selected threshold.
6. The method of claim 5, wherein calculating the variance between each two groups based on the sample probabilities for each gray level comprises:
calculating a set C based on sample probability corresponding to each gray level0And set C1Mean and probability of;
based on set C0And set C1Set of mean and probability calculations C0And set C1The variance between.
7. The method of claim 6, wherein the set C is0The calculation formula of the mean value of (a) is as follows:
Figure FDA0003113318170000021
the set C0The probability of (a) is calculated as follows:
Figure FDA0003113318170000022
the set C1The calculation formula of the mean value of (a) is as follows:
Figure FDA0003113318170000023
the set C1The probability of (a) is calculated as follows:
Figure FDA0003113318170000024
in the above formula,. mu.0Is set C0Mean value of pjSample probability, p, for the jth gray level0Is set C0Probability of (n)jThe number of samples corresponding to the jth gray level, N is the total number of samples in the sample data of the leakage current amplitude value, mu1Is set C1Mean value of p1Is set C1L is the total number of preset gray levels.
8. The method of claim 7, wherein the set C is0And set C1The variance between is calculated as follows:
σ2＝P0(μ0-μ)2+P1(μ1-μ)2
in the above formula, σ2Is set C0And set C1The variance between the values, mu, P, is the mean of all the leakage current amplitude sample data0μ0+P1μ1。
9. An online setting device for a leakage current characteristic threshold, which is characterized by comprising:
the first calculation module is used for dividing the gray level of the sample data of the amplitude value of the leakage current and calculating the sample probability corresponding to each gray level;
the grouping module is used for selecting a plurality of thresholds and respectively grouping the leakage current amplitude sample data into two groups based on the thresholds;
the second calculation module is used for calculating the variance between the two groups based on the sample probability corresponding to each gray level;
and the determining module is used for taking the two groups of corresponding threshold values with the largest variance as the characteristic threshold values of the leakage current of the cable line of the power distribution network.
CN202110654685.1A 2021-06-11 2021-06-11 Online setting method and device for leakage current characteristic threshold Pending CN113552444A (en)

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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117706277A (en) * 2024-02-02 2024-03-15 昆明理工大学 Power distribution network fault line selection method based on graphic analysis and identification

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117706277A (en) * 2024-02-02 2024-03-15 昆明理工大学 Power distribution network fault line selection method based on graphic analysis and identification
CN117706277B (en) * 2024-02-02 2024-06-07 昆明理工大学 Power distribution network fault line selection method based on graphic analysis and identification

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