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Switch cabinet state evaluation method and device

A state assessment, switch cabinet technology, applied in character and pattern recognition, instruments, computer parts, etc., can solve the problems of artificial setting of initial parameters, difficulty in dealing with non-spherical clusters, and the influence of clustering effects, and achieve reasonable improvement. good effect of gender and clustering

Pending Publication Date: 2020-09-29
QINGYUAN POWER SUPPLY BUREAU OF GUANGDONG POWER GRID CO LTD
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] In the clustering evaluation algorithm of switchgear, the status level is divided according to the Euclidean distance, but it is difficult to deal with non-spherical clusters and clusters of different sizes
At the same time, in the state division evaluation of the clustering algorithm, its initial parameters generally need to be set manually, which is likely to have a certain impact on the final clustering effect

Method used

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  • Switch cabinet state evaluation method and device
  • Switch cabinet state evaluation method and device
  • Switch cabinet state evaluation method and device

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0045] figure 1 It is a flow chart of a method for assessing the state of a switchgear provided in Embodiment 1 of the present invention. This embodiment is applicable to evaluating the health state of a switchgear. The method can be performed by a device for evaluating the state of a switchgear, and specifically includes the following steps:

[0046] S110. Obtain live detection data of the switch cabinet.

[0047] Specifically, the faults of the switchgear are mainly insulation faults. Therefore, when evaluating the health status of the switchgear, the insulation state of the switchgear can be mainly evaluated. At this time, the live detection data of the switchgear mainly includes the Insulation state data. For example, the live detection data of the switchgear may include TEV detection data and ultrasonic detection data, which are used to reflect the insulation status of the switchgear. In addition, the TEV test data and ultrasonic test data may include the data of measur...

Embodiment 2

[0055] figure 2 It is a flow chart of a method for evaluating the state of a switchgear provided in Embodiment 2 of the present invention. On the basis of the above embodiments, the method includes:

[0056] S210. Obtain live detection data of the switch cabinet.

[0057] S220. Perform preprocessing on the electrification detection data.

[0058] Specifically, the electrification detection data may include various types of data, and a multi-dimensional feature data set is first constructed for the electrification detection data. For example, live detection data includes TEV detection data, ultrasonic detection data, environmental state temperature data, environmental state humidity data, and historical operation time data. A new data set is established for the above five state feature quantities, and the five sets of feature quantities The data sets are respectively represented by k*1 order column vectors. Exemplarily, the data set of TEV detection data is U=[U (1) u (2)...

Embodiment 3

[0094] image 3 It is a flow chart of a switchgear state evaluation method provided by Embodiment 3 of the present invention. On the basis of the above-mentioned embodiments, the method includes:

[0095] S310. Obtain live detection data of the switch cabinet.

[0096] S320. Using the DBSCAN clustering algorithm to classify the states of the live detection data, so as to determine the states of the switchgear.

[0097] S330. Calculate the silhouette coefficient of the DBSCAN clustering algorithm according to the clusters of the data samples.

[0098] Specifically, calculate the silhouette coefficient of the DBSCAN clustering algorithm according to the clusters of data samples, including:

[0099] Calculate the average distance between the sample points in the cluster and other sample points in the same cluster, which is the intra-cluster dissimilarity of the sample points in the cluster.

[0100] Specifically, the sample point X in the cluster j The average distance to oth...

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Abstract

The invention discloses a switch cabinet state evaluation method and device. The method comprises the following steps: acquiring live detection data of the switch cabinet; carrying out state divisionon the live detection data by adopting a DBSCAN clustering algorithm so as to determine the state of the switch cabinet; and optimizing the parameters of the DBSCAN clustering algorithm through the contour coefficient. The DBSCAN clustering algorithm is adopted to perform state division on the live detection data, so that the data can be classified more scientifically without depending on subjective weights. Moreover, the DBSCAN clustering algorithm can well divide non-spherical clusters and clusters with different sizes, the problem that non-spherical clusters and clusters with different sizes are difficult to process in a common mean clustering algorithm is solved, and more scientific and reasonable operation and maintenance suggestions can be provided for operation and maintenance personnel of the switch cabinet. And then, the parameters of the DBSCAN clustering algorithm are optimized through the contour coefficients, so that the clustering effect of the DBSCAN clustering algorithmis good, and the reasonability of operation and maintenance suggestions is further improved.

Description

technical field [0001] The embodiments of the present invention relate to the technical field of switch cabinet state evaluation, and in particular, to a switch cabinet state evaluation method and device. Background technique [0002] With the continuous development of my country's power grid technology, a large number of switchgear equipment has been integrated into the grid operation, and the operation and maintenance of the switchgear is an important part of the grid operation. Usually, the inside of the switchgear works under the harsh conditions of high temperature, high pressure and high humidity for a long time, and the insulating materials are prone to aging and corrosion. If the loss reaches a certain level, it will be broken down by the high voltage inside the switchgear, resulting in insulation failure of the switchgear. However, the overall structure of the switchgear is relatively complicated, and its live detection data is numerous. At present, there are many ...

Claims

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Application Information

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IPC IPC(8): G06K9/62G06K9/46
CPCG06V10/44G06F18/23G06F18/22
Inventor 胡金磊黎阳羊赖俊驹王伟华耀孙振
Owner QINGYUAN POWER SUPPLY BUREAU OF GUANGDONG POWER GRID CO LTD