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不完备故障类别下基于Multi-SVDD的高压隔离开关故障诊断方法

陈士刚 关永刚 张小青 杨元威 张一茗

电工技术学报2018,Vol.33Issue(11):2439-2447,9.
电工技术学报2018,Vol.33Issue(11):2439-2447,9.DOI:10.19595/j.cnki.1000-6753.tces.180026

不完备故障类别下基于Multi-SVDD的高压隔离开关故障诊断方法

Diagnosis Method of High Voltage Isolating Switch Fault Based on Multi-SVDD under Incomplete Fault Type

陈士刚 1关永刚 2张小青 1杨元威 2张一茗3

作者信息

  • 1. 北京交通大学电气工程学院 北京 100044
  • 2. 电力系统及发电设备控制和仿真国家重点实验室(清华大学电机系) 北京 100084
  • 3. 平高集团有限公司 平顶山 467001
  • 折叠

摘要

Abstract

Focusing on the problem of incomplete fault types existing in high voltage isolating switch fault diagnosis, a fault diagnosis method based on multi-support vector domain description is proposed. Firstly, by principal component analysis to order the normal and known fault samples as a new eigenvector according to their contributions, and the weighted Gaussian kernel function was constructed with the contribution of features to improve the ability to identify inter type feature differences. Then the PSO was used to optimize the kernel parameters so that the model had a higher promotion ability and smaller false positive rate. Secondly, the normal and known fault samples were trained, the hypersphere describing the different working states of the isolating switch was established as the predictive model. Finally, the sample space was divided by multi support vector data description (Multi-SVDD) and the distance from the sample point to the center of the hypersphere was calculated to determine the type of sample. The experimental results showed that this method could effectively deal with the problem of incomplete fault samples in the fault diagnosis of high voltage isolating switch, and it could judge the unknown fault while diagnosing the known fault.

关键词

隔离开关/类别不完备/多重支持向量域/核函数/故障诊断

Key words

Isolating switch/incomplete class/multi support vector data description/kernel function/fault diagnosis

分类

信息技术与安全科学

引用本文复制引用

陈士刚,关永刚,张小青,杨元威,张一茗..不完备故障类别下基于Multi-SVDD的高压隔离开关故障诊断方法[J].电工技术学报,2018,33(11):2439-2447,9.

电工技术学报

OA北大核心CSCDCSTPCD

1000-6753

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