WO2017116090A1

WO2017116090A1 - Gas insulated switchgear partial discharge diagnosis method and device

Info

Publication number: WO2017116090A1
Application number: PCT/KR2016/015216
Authority: WO
Inventors: 김성욱; 정재룡; 김영민
Original assignee: 주식회사 효성
Priority date: 2015-12-31
Filing date: 2016-12-23
Publication date: 2017-07-06
Also published as: KR101729112B1

Abstract

The present invention relates to a gas insulated switchgear partial discharge diagnosis method and device for determining the cause of a partial discharge defect of a gas insulated switchgear by analyzing frequency and phase characteristics of a partial discharge signal. The gas insulated switchgear partial discharge diagnosis method according to the present invention comprises: a partial discharge signal detection step of detecting a partial discharge signal; a partial discharge signal analysis step of analyzing a predetermined frequency and/or phase characteristics of the partial discharge signal without phase synchronization with a phase voltage; and a partial discharge defect cause diagnosis step of diagnosing the cause of a defect of a partial discharge on the basis of the frequency and phase characteristics of the partial discharge signal, which has been analyzed in the partial discharge signal analysis step.

Description

Gas insulation switch partial discharge diagnosis method and device

The present invention relates to a method and an apparatus for diagnosing a partial discharge of a gas insulated switch, and more particularly, to analyze a partial discharge signal to determine a cause of a defect in the partial discharge of the gas insulated switch. That is, the present invention relates to a method and apparatus for diagnosing partial discharge of a gas insulated switchgear capable of determining a cause of a partial discharge defect of a gas insulated switchgear by analyzing frequency and phase characteristics of the partial discharge signal.

Gas Insulated Switchgear refers to a complex switchgear insulated with insulating gas that properly protects the system by opening and closing the line safely in abnormal conditions such as accidents and short circuits, as well as in normal switching in substations.

The gas insulated switchgear is generally configured to include a switchgear and a bus bar such as a disconnector (DS), a ground switch (ES), and a breaker (CB) in a metal enclosure filled with insulating gas.

Recently, UHF (Ultra High Frequency) Partial Discharge (SH) sensors have been applied to various gas insulated switchgear as an error diagnosis tool for gas insulated switchgear.

In general, a gas insulated switch is composed of an insulating material such as epoxy, which connects a cylindrical metal enclosure at an appropriate interval, and when a partial discharge occurs inside a gas insulated switchgear, UHF partial discharge electromagnetic waves radiate to the outside through the spacer. Attach the partial discharge detection sensor to the outside of the spacer by using the leaking point, detect the electromagnetic wave generated inside the gas insulated switchgear, and remove the noise mixed in the detection signal to diagnose the abnormality such as the degree of deterioration, and repair or replace it. In order to estimate the timing, many studies have been conducted on the diagnostic device or method of such a gas insulated switchgear.

For example, Korean Patent Publication No. 10-2009-0075657 discloses a partial discharge detection sensor for detecting a partial discharge, a noise detection sensor for detecting noise, and a partial discharge data and noise when a partial discharge occurs due to an abnormal defect in the GIS. A gas insulated switch diagnostic device including a synchronization device for outputting data in synchronization with a frequency of a phase voltage is presented.

However, even in this case, the partial discharge signal may be diagnosed only after synchronizing with the phase voltage, and thus, there is a disadvantage in that the risk that may occur in the process of synchronizing with the phase voltage is not prevented.

It is an object of the present invention to provide a gas discharge switch partial discharge diagnosis method and apparatus capable of diagnosing the cause of a partial discharge defect by analyzing the frequency and phase characteristics of the partial discharge signal without phase voltage and phase synchronization.

Another object of the present invention is to provide a method and apparatus for diagnosing partial discharge of a gas insulated switchgear capable of diagnosing a cause of a partial discharge without phase voltage and phase synchronization, and thus preventing a risk that may occur in the process of synchronizing with phase voltage. There is this.

In the gas discharge switch partial discharge diagnosis method according to the present invention, a partial discharge signal detecting step of detecting a partial discharge signal, a partial discharge analyzing at least one of predetermined frequency and phase characteristics of the partial discharge signal without phase voltage and phase synchronization The signal analysis step and the partial discharge signal analysis step may include a partial discharge defect cause diagnosis step of diagnosing the cause of the partial discharge defect based on the frequency and phase characteristics of the partial discharge signal analyzed.

Here, the partial discharge signal analysis step may include a frequency distribution discrimination step for distinguishing a frequency distribution including the partial discharge signal, a maximum value measurement step for distinguishing the maximum magnitude among the partial discharge signals, a first maximum magnitude frequency and a second maximum magnitude of the partial discharge signal. Distinguishing the frequency distribution of the maximum magnitude frequency to distinguish the frequency distribution of the maximum magnitude frequency, distinguishing the maximum difference of the maximum magnitude frequency by frequency distribution to distinguish the maximum difference of the maximum magnitude by frequency distribution including the partial discharge signal, and partial discharge The frequency distribution may include a density discrimination step for distinguishing the density of the partial discharge signal for each frequency distribution including the signal.

In addition, at least one frequency distribution discrimination step may distinguish the frequency distribution.

Here, the maximum value measuring step may measure the maximum magnitude value of the partial discharge signal.

In addition, the step of discriminating the frequency distribution of the maximum magnitude frequency may distinguish a frequency distribution including the largest first largest magnitude frequency and the next largest largest magnitude frequency.

Here, in the step of distinguishing the maximum difference of the maximum magnitude frequencies for each frequency distribution, the difference between the largest magnitude and the smallest magnitude between the maximum magnitude frequencies for each frequency distribution may be distinguished.

In addition, the density discrimination step for each frequency distribution may distinguish the density based on the number of detection signals for each frequency distribution.

Here, the partial discharge signal analysis step includes a phase cluster number discrimination step of distinguishing the number of phase clusters with respect to the maximum magnitude frequency of the partial discharge signal, and a phase full range for distinguishing phase ranges in which phases are distributed with respect to the maximum magnitude frequency of the partial discharge signal. Phase differentiation phase discrimination phase phase for distinguishing the phase ranges distributed by phase clusters for the maximum magnitude frequency of the partial discharge signal, phase density density for phase clustering to distinguish the signal density per phase cluster for the maximum magnitude frequency of the partial discharge signal Phase difference measuring phase difference for each phase cluster for measuring the difference in the maximum magnitude between phase clusters for the maximum magnitude frequency of the partial discharge signal, and phase clustering for distinguishing the shape of the phase cluster for the maximum magnitude frequency of the partial discharge signal. It may be made of a shape distinguishing step.

In addition, the phase cluster number discrimination step may distinguish the number of clusters when clusters are clearly distinguished, and may distinguish noises when the number of clusters is 3 or more.

Here, the phase full range discrimination step may distinguish whether or not the phase range occurs over the entire phase.

In addition, the step of distinguishing the range by phase cluster may distinguish at least one of whether the phase range exceeds 90 degrees or not and whether there is a phase cluster that can be distinguished.

Here, the density discrimination step for each phase group may distinguish the density based on the number of signals for each phase group.

In addition, the step of measuring the maximum magnitude difference for each phase cluster may distinguish a difference between the largest magnitude and the smallest magnitude between the phase magnitude maximum phases.

Here, the phase cluster shape distinguishing step may distinguish one or more of a similar cluster number, a cluster unknown, and no cluster by distinguishing between similarities with at least one preset cluster.

In addition, the cause of the defect of the partial discharge is a portion including at least one of floating, void, transformer fault (TR Fault), conductor protrusion (protrusion), cracks, free particles (free particles) The cause of the discharge defect or the noise defect including at least one of an external corona, external noise, a sensor connector fault, and a mobile phone signal may be included.

In addition, the gas insulated switchgear partial discharge diagnostic apparatus includes a partial discharge signal detector for detecting a partial discharge signal, a partial discharge signal analyzer for analyzing at least one of predetermined frequency and phase characteristics of the partial discharge signal without phase voltage and phase synchronization And a partial discharge defect cause diagnosis unit for diagnosing a cause of a partial discharge defect based on predetermined frequency and phase characteristics of the partial discharge signal analyzed by the partial discharge signal analyzer.

Here, the partial discharge signal analysis unit for frequency analysis of the partial discharge signal, the frequency distribution including the partial discharge signal, the maximum magnitude of the partial discharge signal, the frequency of the first maximum magnitude frequency and the second maximum magnitude frequency of the partial discharge signal It is possible to distinguish the distribution, the maximum difference of the maximum magnitude for each frequency distribution including the partial discharge signal, and the density of the partial discharge signal for each frequency distribution including the partial discharge signal.

In addition, the partial discharge signal analysis unit, for phase analysis of the partial discharge signal, the number of phase clusters, the phase range in which the phase is distributed, the phase range distributed by the phase cluster, and the signal density by phase cluster for the maximum magnitude frequency of the partial discharge signal. , The difference in maximum magnitude between the phase clusters, and the shape of the phase clusters can be distinguished.

The method and apparatus for diagnosing a partial discharge of a gas insulated switch according to the present invention have an advantage of determining a cause of a defect for the partial discharge of the gas insulated switch by analyzing the partial discharge signal.

Alternatively, the method and apparatus for diagnosing the partial discharge of the gas insulated switch according to the present invention analyze the frequency and phase characteristics of the partial discharge signal to determine the cause of the partial discharge defect of the gas insulated switch and diagnose the cause of the partial discharge without the phase voltage and phase synchronization. There is an advantage that can prevent the risk that can occur in the process of synchronizing with the phase voltage.

1 is a flowchart illustrating a gas discharge switch partial discharge diagnosis method according to an embodiment of the present invention.

FIG. 2 is a flow chart showing in more detail the frequency characteristic analysis of the partial discharge signal analysis step of FIG.

3 is a table used for frequency characteristic analysis of the partial discharge signal analysis step of FIG.

4 is a frequency spectrum illustrating an example of analyzing frequency characteristics in the partial discharge signal analysis step of FIG. 1.

FIG. 5 is a flowchart illustrating in more detail a phase characteristic analysis of the partial discharge signal analysis step of FIG. 1.

6 is a table used for phase characteristic analysis of the partial discharge signal analysis step of FIG.

7 is a phase spectrum illustrating an example of analyzing phase characteristics in the partial discharge signal analysis step of FIG. 1.

8 is a flow chart illustrating in detail the entire flow of FIG. 1.

FIG. 9 is a flowchart illustrating an example of diagnosing a defect cause of partial discharge in the partial discharge defect cause diagnosis step of FIG. 1.

FIG. 10 is a table illustrating an example of a cause of a partial discharge defect determined in the partial discharge defect cause diagnosis step of FIG. 1.

11 is a block diagram showing a gas discharge switch partial discharge diagnostic apparatus according to an embodiment of the present invention.

Specific embodiments of the present invention will be described with reference to the accompanying drawings.

As the invention allows for various changes and numerous embodiments, particular embodiments will be illustrated in the drawings and described in detail in the written description. It is not intended to limit the invention to the specific embodiments, it can be understood to include all changes, equivalents, and substitutes included in the spirit and scope of the present invention.

Hereinafter, a method and apparatus for diagnosing partial discharge of a gas insulated switch according to the present invention will be described in detail with reference to the accompanying drawings.

1 is a flowchart illustrating a method for diagnosing partial discharge of a gas insulated switch according to an embodiment of the present invention, and FIGS. 2 to 10 are flowcharts, tables, and spectra for explaining FIG. 1 in detail.

Hereinafter, a method of diagnosing a partial discharge of a gas insulated switch according to an embodiment of the present invention will be described with reference to FIGS. 1 to 10.

First, referring to FIG. 1, the gas insulation switch partial discharge diagnosis method according to an exemplary embodiment of the present invention includes detecting a partial discharge signal (S100), a predetermined frequency for the partial discharge signal without phase voltage and phase synchronization, and Analyzing at least one of the phase characteristics (S200), and diagnosing the cause of the defect of the partial discharge based on the frequency and phase characteristics of the partial discharge signal analyzed in the partial discharge signal analysis step (S200) (S300). do.

In addition, the cause of the defect of the partial discharge is a portion including at least one of floating, void, transformer fault (TR Fault), conductor protrusion (protrusion), cracks, free particles (free particles) The cause of the discharge defect or the noise defect including at least one of an external corona, external noise, a sensor connector fault, and a mobile phone signal is included.

In detail, in the partial discharge signal detection step S100, the partial discharge signal is detected from the gas insulated switchgear, and in the partial discharge signal analysis step S200, the frequency and phase characteristics of the partial discharge signal are analyzed without phase synchronization of the phase voltage. The effect is to avoid the risks that can arise from synchronizing with the voltage.

In addition, by sequentially inputting frequency and phase characteristics in the step S300 of diagnosing the cause of the partial discharge defect, there is an advantage of easily determining the cause of the partial discharge defect such as partial discharge and noise.

2 to 4 illustrate a method of analyzing the frequency characteristic of the partial discharge signal, and FIGS. 5 to 7 illustrate a method of analyzing the phase characteristic of the partial discharge signal. 8 to 10 exemplarily illustrate a method of determining a cause of a defect of a partial discharge signal based on the frequency and phase characteristics of the partial discharge signal.

FIG. 2 is a flowchart illustrating in detail the frequency characteristic analysis of the partial discharge signal analysis step S200 of FIG. 1.

As can be seen in Figure 2, the partial discharge signal analysis step (S200) is the step of distinguishing the frequency distribution including the partial discharge signal (S211), the step of distinguishing the maximum size of the partial discharge signal (S212), partial discharge Distinguishing the frequency distribution of the first maximum magnitude frequency and the second maximum magnitude frequency of the signal (S213), distinguishing the maximum difference of the maximum magnitude for each frequency distribution including the partial discharge signal (S214), and the partial discharge signal It includes a step (S215) to distinguish the density of the partial discharge signal for each frequency distribution included.

In addition, the frequency distribution discrimination step S211 distinguishes the frequency distribution with at least one.

Here, the maximum value measuring step S212 measures the maximum magnitude value of the partial discharge signal.

In addition, the step S213 of distinguishing the frequency distribution of the maximum magnitude frequency distinguishes the frequency distribution including the largest first magnitude frequency and the second largest magnitude frequency.

Here, in step S214, the maximum difference between the maximum magnitude frequencies for each frequency distribution is distinguished between the largest magnitude and the smallest magnitude difference between the maximum magnitude frequencies for each frequency distribution.

In addition, the density discrimination step for each frequency distribution (S215) distinguishes the density based on the number of detection signals for each frequency distribution.

For example, in the frequency distribution discrimination step (S211), the frequency distribution is divided into F1, F2, and F3 to indicate whether a frequency distribution including the partial discharge signal is included or included in all frequencies, and the maximum value measurement step (S212) is performed. The maximum size can be measured at.

On the other hand, in the step of distinguishing the frequency distribution of the maximum magnitude frequency (S213), it is distinguished in which frequency distribution of the first maximum magnitude frequency and the second maximum magnitude frequency are in F1, F2, and F3, and distinguishes the maximum difference of the maximum magnitude frequency by frequency distribution. In step S214, the maximum difference among the maximum size at F1, the maximum size at F2, and the maximum size at F3 is distinguished.

In the density discrimination step according to the frequency distribution (S215), the number of partial discharge signals may be distinguished by F1, F2, and F3, and thus may be classified into high, medium, low, and none.

3 is a table used for frequency characteristic analysis of the partial discharge signal analysis step (S200) of FIG. 1. As can be seen in Figure 3, the frequency characteristics for the partial discharge signal is largely 'distribution' distinguished in the frequency distribution discriminating step (S211), the 'maximum value (maximum) measured in the maximum value measuring step (S212) magnitude ',' maximum magnitude distribution 'distinguishing in the frequency distribution discrimination step of the maximum magnitude frequency (S213), and' Peak difference ( Difference ”and“ Density ”which are distinguished in the density discrimination step for each frequency distribution (S215).

In detail, 'distribution' distinguishes all frequency ranges or specific ranges, 'maximum magnitude' measures values of maximum magnitude, and 'maximum magnitude distribution' Distinguishes the distribution of the first largest magnitude and the next largest frequency distribution of the second largest magnitude, and 'Peak Difference' indicates whether the difference between the first largest magnitude and the second largest magnitude is large or small. The 'density' can distinguish whether the number of signals included in each frequency distribution is high, medium, low, or absent.

4 is a frequency spectrum showing an example of analyzing frequency characteristics in the partial discharge signal analysis step (S200) of FIG. 1. As can be seen in Figure 4, according to the classification method of the density discrimination step (S215) for each frequency distribution, (a) is a high density, (b) is a medium density, (c) is a density It is understood that is a low case and (d) indicates a case where there is no density.

FIG. 5 is a flowchart illustrating in detail the phase characteristic analysis of the partial discharge signal analysis step S200 of FIG. 1.

As can be seen in Figure 5, the partial discharge signal analysis step (S200) is a step of distinguishing the number of phase clusters with respect to the maximum magnitude frequency of the partial discharge signal (S221), the phase distribution for the maximum magnitude frequency of the partial discharge signal Distinguishing the phase ranges (S222), distinguishing the phase ranges distributed by phase clusters with respect to the maximum magnitude frequency of the partial discharge signal (S223), and determining the signal density for each phase cluster with respect to the maximum magnitude frequency of the partial discharge signal. Distinguishing (S224), measuring the difference in the maximum magnitude between the phase clusters with respect to the maximum magnitude frequency of the partial discharge signal (S225), and discriminating the shape of the phase cluster with respect to the maximum magnitude frequency of the partial discharge signal ( S226).

In addition, the phase cluster number discrimination step (S221) distinguishes the number of clusters when the clusters are clearly distinguished, and distinguishes them by noise when the number of clusters is 3 or more.

Here, the phase full range discrimination step S222 distinguishes whether or not the phase range occurs over the entire phase.

In addition, the phase discrimination range distinction step (S223) distinguishes at least one of the presence or absence of a phase cluster that can be distinguished from whether or not the phase range exceeds 90 degrees.

Here, in the density discrimination step S224, the density is distinguished based on the number of signals for each phase group.

In addition, the step of measuring the maximum size difference for each phase cluster (S225) distinguishes the difference between the largest size and the smallest size between the maximum size phases for each phase group.

Here, the phase cluster shape distinguishing step (S226) distinguishes one or more of a similar cluster number, a cluster unclear, and no cluster by distinguishing between similarities with at least one preset cluster.

For example, in the phase cluster number discrimination step (S221), when the number of phase clusters is distinguished and indicates that the number of phase clusters is one or indefinite, it is expressed as one, and when two phase clusters are detected as the first cluster and the second cluster, respectively. It can be expressed in two and can be distinguished by noise when the number of phase clusters is three or more.

In the phase full range discrimination step (S222), it is determined whether a phase with respect to the maximum magnitude frequency of the partial discharge has occurred over the entire phase range. In addition, in the step of distinguishing the phase groups by phase cluster (S223), phase widths of the phase clusters may be distinguished, and whether the first cluster and the second cluster exceed 90 degrees and the case where there is no phase cluster. In the density discrimination step (S224) according to the phase clusters, high, medium, low, or none may be distinguished based on the number of phase patterns detected for the first and second clusters.

Meanwhile, in the maximum size difference measurement step for each phase cluster (S225), it may be determined whether the peak difference between the first and second clusters is large or small, and in the phase cluster shape distinguishing step (S226), the phase cluster shape is 1 to 11. At least one cluster shape, such as a burn, may be pre-stored and compared with a stored cluster shape to distinguish between similarly shaped cluster shapes, or to distinguish a cluster from an unknown or phased cluster.

FIG. 6 is a table used for phase characteristic analysis in the partial discharge signal analysis step S200 of FIG. 1. As can be seen in Figure 6, the phase characteristics for the partial discharge signal is largely 'group distribution' distinguished in the phase cluster number discrimination step (S221), 'differentiated in the phase full range discrimination step (S222) 'Full range', 'partial range' distinguished in the range discrimination by phase cluster (S223), 'density', phase cluster distinguished in the density discrimination step (S224) by phase cluster It may be distinguished by 'magnitude' distinguished in the maximum size difference measurement step S225, and 'shape' distinguished in the phase cluster shape discrimination step S226.

Specifically, 'group distribution' distinguishes the number of clusters in which a phase is distributed, 'full range' distinguishes whether a distinct cluster is distributed over the entire phase, partial range) distinguishes whether or not a cluster is greater than or equal to 90 degrees or less, or 90 degrees is an example, and may be changed to 180 or 270 depending on the case.

Meanwhile, 'Density' is classified into high, medium, low, or none by the number of signals occupied for the first and second clusters, and Magnitude is the difference in magnitude between peaks of the clusters. 'Shape' can distinguish between the cluster shape number of each cluster or the case where the cluster has no opacity or phase cluster.

FIG. 7 is a phase spectrum illustrating an example of analyzing phase characteristics in the partial discharge signal analysis step S200 of FIG. 1. As can be seen in FIG. 7, phase clusters classified in the phase cluster number discrimination step S221 may be divided into two groups, such as the phase group 610 and 620, and the phase group may be divided through the phase full range discrimination step S222. It can be seen that 610 and 620 do not occur in potential phase.

In addition, the phase occupancy ranges of the phase group 610 and the 620 are greater than 90 degrees through the phase group-specific range discrimination step S223, and the phase group 610 is determined through the phase discrimination phase distinction step S224. It can be seen that the silver density is high and the density 620 is divided into the middle of the phase group 610.

On the other hand, the difference in the maximum size of each phase group through the step of measuring the maximum size difference for each phase group (S225) can be seen as similar.

8 is a flow chart illustrating in detail the entire flow of FIG. 1. As can be seen in Figure 8, the partial discharge defect cause diagnosis step (S300) is to input the results analyzed in the partial discharge signal analysis step (S200) one by one to diagnose the cause of the defect of the partial discharge.

For example, in the step S300 of diagnosing the cause of the partial discharge defect, as a phase characteristic, the number of phase clusters in the phase cluster number discrimination step S221, the phase range in phase full range discrimination step S222, and the range discrimination phase for each phase cluster are determined. Range by phase cluster in step S223, density discrimination by phase cluster in step S224, density difference by phase cluster in phase cluster, maximum size difference by phase cluster in phase cluster in step S225, phase cluster shape distinction In step S226, the phase cluster stars and the like are input in order.

In addition, as the frequency characteristic, the frequency distribution in the frequency distribution discrimination step S211, the maximum magnitude frequency magnitude in the maximum value measurement step S212, and the frequency distribution of the maximum magnitude frequency in the frequency distribution discrimination step S213 of the maximum magnitude frequency. Partial discharge by inputting the maximum difference of the maximum magnitude frequency by frequency distribution in step S214, the maximum difference of frequency by frequency distribution, and the density by frequency distribution in step S215 The cause of the fault can be diagnosed automatically.

9 is a flowchart illustrating an example of diagnosing a cause of a partial discharge defect in the partial discharge defect cause diagnosis step S300 of FIG. 1. As can be seen in FIG. 9, the cluster shape is divided into two according to the input of the phase cluster, the cluster shape is distinguished by 1-1, the frequency distribution is at all frequencies, and the density is all at the frequency distributions F1, F2, and F3. If is equal to or more than 18, it indicates that the cause of the defect of the partial discharge is determined as a floating, external corona, transformer defect (TR defect), sensor abnormality, void, or the like.

FIG. 10 is a table illustrating an example of a cause of a partial discharge defect determined in the partial discharge defect cause diagnosis step S300 of FIG. 1. As can be seen in Figure 10, the cause of the fault of the partial discharge is floating, void (void), transformer fault (TR Fault), the protrusion (protrusion), crack (cracks), free particles (free particles) Cause of partial discharge fault including at least one, or cause of noise fault including at least one of external corona, external noise, sensor connector fault, and mobile phone signal It can be divided into.

As can be seen in FIG. 11, the gas insulated switchgear partial discharge diagnosis apparatus includes a partial discharge signal detector 100 detecting a partial discharge signal, at least one of predetermined frequency and phase characteristics of the partial discharge signal without phase voltage and phase synchronization. A partial discharge defect for diagnosing a cause of a partial discharge based on a predetermined frequency and phase characteristics of the partial discharge signal analyzer 200 for analyzing any one of the partial discharge signals analyzed by the partial discharge signal analyzer 200 and the partial discharge signal analyzer 200. Cause diagnosis unit 300 is included.

Here, the partial discharge signal analysis unit 200, for frequency analysis of the partial discharge signal, the frequency distribution including the partial discharge signal, the maximum magnitude of the partial discharge signal, the first maximum magnitude frequency and the second maximum of the partial discharge signal The frequency distribution of the magnitude frequency, the maximum difference of the maximum magnitude of each frequency distribution including the partial discharge signal, and the density of the partial discharge signal according to the frequency distribution including the partial discharge signal are distinguished.

In addition, the partial discharge signal analyzer 200 performs phase analysis on the maximum magnitude frequency of the partial discharge signal in order to analyze the phase of the partial discharge signal. The signal density per cluster, the difference in maximum magnitude between phase clusters, and the shape of phase clusters are distinguished.

And cause a partial discharge fault including at least one of floating, voids, transformer faults, TR, faults, protrusions, cracks, and free particles, or an external corona. It may be classified as a cause of noise defect including at least one of an external corona, an external noise, a sensor connector fault, and a mobile phone signal.

In the gas insulated switchgear partial discharge diagnosis apparatus of the present invention, the partial discharge signal detection unit 100 detects the partial discharge signal from the gas insulated switchgear, and the partial discharge signal analysis unit 200 is applied to the partial discharge signal without phase synchronization of phase voltage. By analyzing the frequency and phase characteristics as described above, the cause of the partial discharge defect or the noise defect can be diagnosed, thereby preventing the risk that may occur in the process of synchronizing with the phase voltage. As described above, the method and device for diagnosing the partial discharge of the gas insulated switch according to the present invention can diagnose the cause of the partial discharge by analyzing the frequency and phase characteristics of the partial discharge signal without the phase voltage and the phase synchronization. The cause of faults in partial discharge can be diagnosed without overphase synchronization, thus avoiding the risks that can occur during synchronization with phase voltage.

What has been described above includes examples of one or more embodiments. Of course, not all possible combinations of components or methods may be described for the purpose of describing the above-described embodiments, but those skilled in the art will recognize that many further combinations and substitutions of various embodiments are possible. Accordingly, the described embodiments are intended to embrace all such alterations, modifications and variations that fall within the spirit and scope of the appended claims.

The present invention relates to a gas insulated switch partial discharge diagnostic method and apparatus, which can be used in the field of gas insulated switch.

Claims

A partial discharge signal detecting step of detecting the partial discharge signal;

A partial discharge signal analyzing step of analyzing at least one of predetermined frequency and phase characteristics of the partial discharge signal without phase voltage and phase synchronization; And

And a partial discharge defect cause diagnosis step of diagnosing the cause of the partial discharge defect based on the frequency and phase characteristics of the partial discharge signal analyzed in the partial discharge signal analysis step.
The method of claim 1,

The partial discharge signal analysis step,

A frequency distribution discrimination step of distinguishing a frequency distribution including the partial discharge signal;

A maximum value measuring step of discriminating a maximum magnitude among the partial discharge signals;

Discriminating a frequency distribution of a maximum magnitude frequency to distinguish a frequency distribution of a first maximum magnitude frequency and a second maximum magnitude frequency of the partial discharge signal;

Distinguishing the maximum difference of the maximum magnitude frequency of each frequency distribution for distinguishing the maximum difference of the maximum magnitude of each frequency distribution including the partial discharge signal; And

Density discrimination for each frequency distribution for distinguishing the density of the partial discharge signal for each frequency distribution containing the partial discharge signal; Gas insulation switch partial discharge diagnostic method comprising a.
The method of claim 2,

The frequency distribution distinguishing step, the gas insulated switchgear partial discharge diagnostic method, characterized in that for distinguishing the frequency distribution with at least one.
The method of claim 2,

The measuring of the maximum value, the partial discharge diagnostic method of gas insulated switch, characterized in that for measuring the maximum magnitude value of the partial discharge signal.
The method of claim 2,

The step of distinguishing the frequency distribution of the maximum magnitude frequency, the gas insulated switchgear, characterized in that for distinguishing the frequency distribution including the first largest magnitude frequency and the second largest magnitude frequency that is the largest magnitude; Partial discharge diagnostic method.
The method of claim 2,

Distinguishing the maximum difference of the maximum magnitude frequency for each frequency distribution, the gas discharge switch partial discharge diagnostic method, characterized in that for distinguishing the difference between the largest magnitude and the smallest magnitude between the maximum magnitude frequency for each frequency distribution.
The method of claim 2,

The density discrimination step for each frequency distribution, the gas insulated switchgear partial discharge diagnostic method, characterized in that for distinguishing the density based on the number of detection signals for each frequency distribution.
The method of claim 1,

The partial discharge signal analysis step,

A phase cluster number discrimination step of discriminating the number of phase clusters with respect to the maximum magnitude frequency of the partial discharge signal;

A phase full range discrimination step of distinguishing a phase range in which phases are distributed with respect to a maximum magnitude frequency of the partial discharge signal;

A phase group-specific range discrimination step of distinguishing a phase range distributed for each phase group with respect to the maximum magnitude frequency of the partial discharge signal;

A density discrimination phase for each phase cluster for distinguishing signal density for each phase cluster with respect to the maximum magnitude frequency of the partial discharge signal;

Measuring a maximum magnitude difference for each phase group for measuring a difference in maximum magnitude between phase clusters with respect to the maximum magnitude frequency of the partial discharge signal; And

And a phase cluster shape discrimination step of distinguishing a shape of a phase cluster with respect to the maximum magnitude frequency of the partial discharge signal.
The method of claim 8,

The phase cluster number distinguishing step may include distinguishing the number of clusters when the clusters are clearly distinguished and distinguishing them by noise when the number of clusters is 3 or more.
The method of claim 8,

The phase full range discrimination step, the gas insulated switchgear partial discharge diagnostic method, characterized in that for distinguishing whether the phase range occurs over the entire phase.
The method of claim 8,

In the phase discrimination range distinction step, the gas insulated switchgear partial discharge diagnostic method, characterized in that for distinguishing at least any one of the presence or absence of a phase cluster that can be distinguished from the phase range exceeds 90 degrees.
The method of claim 8,

The density discrimination step for each phase group, the gas insulated switchgear partial discharge diagnostic method, characterized in that for distinguishing the density based on the number of signals for each phase group.
The method of claim 8,

Measuring the maximum magnitude difference for each phase group, gas discharge switch partial discharge diagnostic method, characterized in that for distinguishing the difference between the largest magnitude and the smallest magnitude between the maximum magnitude phase for each phase group.
The method of claim 8,

The phase cluster shape distinguishing step may distinguish one or more of a similar group number, a cluster unknown, and no cluster by distinguishing between similarities with at least one predetermined cluster.
The method of claim 1,

The cause of the partial discharge may include at least one of floating, void, transformer fault, TR, fault, crack, and free particles. A cause of a discharge defect or a noise defect including at least one of an external corona, an external noise, a sensor connector fault, and a mobile phone signal. Gas discharge switch partial discharge diagnosis method.
A partial discharge signal detector for detecting a partial discharge signal;

A partial discharge signal analyzer configured to analyze at least one of predetermined frequency and phase characteristics of the partial discharge signal without phase voltage and phase synchronization; And

A partial discharge fault cause diagnosis unit for diagnosing a cause of a partial discharge defect based on a predetermined frequency and phase characteristic of the partial discharge signal analyzed by the partial discharge signal analyzer; Diagnostic device.
The method of claim 16,

The partial discharge signal analysis unit,

For frequency analysis of the partial discharge signal, a frequency distribution including the partial discharge signal, the maximum magnitude of the partial discharge signal, the frequency distribution of the first maximum magnitude frequency and the second maximum magnitude frequency of the partial discharge signal, A gas insulated switchgear partial discharge diagnostic apparatus, characterized in that for distinguishing the maximum difference of the maximum magnitude for each frequency distribution including the partial discharge signal, and the density of the partial discharge signal for each frequency distribution containing the partial discharge signal.
The method of claim 16,

The partial discharge signal analysis unit,

For phase analysis on the partial discharge signal, the number of phase clusters, phase ranges in which phases are distributed, phase ranges distributed by phase clusters, signal density per phase clusters, and maximum between phase clusters for the maximum magnitude frequency of the partial discharge signals. A gas insulated switchgear partial discharge diagnostic apparatus characterized by distinguishing a difference in size and a shape of a phase cluster.