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Improved GIS equipment abnormal sound vibration identification method based on particle swarm algorithm

A particle swarm algorithm and identification method technology, applied in the field of abnormal noise and vibration identification of GIS equipment improved based on particle swarm algorithm, can solve problems such as accurate positioning and rapid repair difficulties, achieve important significance and practical value, high identification accuracy, Identify significant effects

Active Publication Date: 2021-01-08
STATE GRID CHONGQING ELECTRIC POWER CO ELECTRIC POWER RES INST +1
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  • Abstract
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  • Claims
  • Application Information

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Problems solved by technology

However, due to its fully enclosed structure, it is difficult to accurately locate and quickly repair once a fault occurs

Method used

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  • Improved GIS equipment abnormal sound vibration identification method based on particle swarm algorithm
  • Improved GIS equipment abnormal sound vibration identification method based on particle swarm algorithm
  • Improved GIS equipment abnormal sound vibration identification method based on particle swarm algorithm

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Embodiment Construction

[0032] One of the purposes of the present invention is to propose a group of discriminative vibration feature quantities for the abnormal noise and vibration of GIS equipment; Fault detection and identification method of ringing vibration.

[0033] Such as figure 2 Shown, general idea of ​​the present invention is as follows:

[0034] S1, constructing the vibration training sample set and the vibration test sample set of different contact states of the GIS equipment isolating switch; the vibration training sample set and the vibration test sample set are constructed by existing algorithms;

[0035] S2. Using the EEMD algorithm to obtain the IMF modal component of the defect vibration signal, the defect vibration signal comes from the vibration training sample set and the vibration test sample set of different contact states of the isolation switch of the GIS equipment;

[0036] S3. Extract the energy ratio K according to the relative size of the defect vibration signal betw...

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PUM

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Abstract

The invention discloses an improved GIS equipment abnormal sound vibration identification method based on a particle swarm algorithm, which belongs to the technical field of GIS equipment fault detection and identification, and comprises the following steps: optimizing parameters of an LSSVM by adopting an ILPSO algorithm to obtain an ILPSO-LSSVM algorithm, and constructing a GIS equipment isolation switch contact state identification model by combining the ILPSO-LSSVM algorithm and a training sample set combined feature matrix; and carrying out validity verification on the GIS equipment isolation switch contact state identification model by adopting the constructed test sample set combination characteristic matrix, and the like. The improved least square support vector machine model basedon the particle swarm algorithm is constructed through optimization design of a traditional SVM model, and the model is high in recognition accuracy and small in average standard deviation.

Description

technical field [0001] The invention relates to the technical field of GIS equipment fault detection and identification, in particular to an improved GIS equipment abnormal noise and vibration identification method based on particle swarm algorithm. Background technique [0002] Gas insulated switchgear (GIS) is widely used in power grids. It combines circuit breakers, disconnectors, grounding switches, voltage and current transformers, lightning arresters, busbars, bushings and other primary equipment into a whole in an orderly manner, and is packaged in a metal shell and filled with SF6 gas as an extinguishing A closed combined electrical appliance composed of an arc and an insulating medium. Compared with traditional open equipment, GIS equipment occupies a small area, has high reliability, strong security, and less operation and maintenance workload. However, due to its fully enclosed structure, once a fault occurs, it is difficult to accurately locate and quickly repa...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F30/27G06K9/62G06F119/10G06F119/02
CPCG06F30/27G06F2119/10G06F2119/02G06F18/2411
Inventor 蒋西平李永福郝建王旭鹏钟尧王谦龙英凯李思全罗骁枭
Owner STATE GRID CHONGQING ELECTRIC POWER CO ELECTRIC POWER RES INST
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