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Research on Mechanical Fault Recognition of Circuit Breaker Based on SVM

机译:基于SVM的断路器机械故障识别研究。

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摘要

The on-line fault recognition for Circuit Breakers (CBs) is very important when the condition monitoring of CBs is realized. In this paper, a new efficiency fault recognition method is provided, by using Support Vector Machines (SVMs). ANN and SVM are compared on their recognition accuracy, which shows that the SVM is more efficient. The algorithm of SVM is improved, and the improved SVM can obtain higher recognition accuracy.
机译:实现断路器状态监控时,断路器的在线故障识别非常重要。本文利用支持向量机(SVM)提供了一种新的效率故障识别方法。比较了人工神经网络和支持向量机的识别精度,表明支持向量机的效率更高。对支持向量机的算法进行了改进,改进后的支持向量机可以获得较高的识别精度。

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  • 来源
    《電子情報通信学会技術研究報告》 |2009年第287期|p.149-152|共4页
  • 作者单位

    State Key Lab of Electrical Insulation and Power Equipment, Xi'an Jiaotong University, Xi'an, 710049, China;

    State Key Lab of Electrical Insulation and Power Equipment, Xi'an Jiaotong University, Xi'an, 710049, China;

    State Key Lab of Electrical Insulation and Power Equipment, Xi'an Jiaotong University, Xi'an, 710049, China;

    State Key Lab of Electrical Insulation and Power Equipment, Xi'an Jiaotong University, Xi'an, 710049, China;

    State Key Lab of Electrical Insulation and Power Equipment, Xi'an Jiaotong University, Xi'an, 710049, China;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    circuit breakers; fault recognition; SVM; mechanical fault;

    机译:断路器;故障识别;支持向量机;机械故障;

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