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文章摘要
级联SVG逆变器的IGBT开路故障诊断研究
Research on Open Circuit Fault Diagnosis of Cascade SVG Inverter IGBT
Received:March 05, 2014  Revised:October 12, 2014
DOI:
中文关键词: SVG  IGBT  FFT  神经网络  故障诊断
英文关键词: SVG  IGBT  FFT  the neural network  fault diagnosis  
基金项目:国家教育部博士点基金
Author NameAffiliationE-mail
HAN Li School of Information and Electrical Engineering China University of Mining and Technology Xuzhou 221008 Jiangsu,China dannyli717@163.com 
LUO Peng* School of Information and Electrical Engineering China University of Mining and Technology Xuzhou 221008 Jiangsu,China dqluopeng@163.com 
YU Ting School of Information and Electrical Engineering China University of Mining and Technology Xuzhou 221008 Jiangsu,China  
SHI Li-ping School of Information and Electrical Engineering China University of Mining and Technology Xuzhou 221008 Jiangsu,China  
LI Jia-jia School of Information and Electrical Engineering China University of Mining and Technology Xuzhou 221008 Jiangsu,China  
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中文摘要:
      为了实现SVG逆变器中的IGBT开路故障的定位,提出了基于FFT分析和神经网络的故障诊断方法。该方法首先利用FFT分析技术,对H桥逆变器的输出的电压信号进行FFT分析,找出各次谐波含有率的规律,将谐波含有率较高的谐波作为特征信号。最后利用BP神经网络方法,实现了故障元件的定位。在Matlab搭建的级联SVG逆变器的IGBT开路故障系统中进行仿真实验验证。仿真实验结果表明,本文所提出的故障诊断方法能有效实现故障元件的定位。
英文摘要:
      In order to achieve recognize the IGBT faults of SVG inverter, a method for fault diagnosis is proposed based on FFT analysis and the neural network. Firstly, using FFT analysis to ananlysis the H inverter output voltage signal , finding the harmonic content of the rule, the higher the harmonic content of the signal is put as a characteristic harmonics. Finally, the neural network is used to achieve the positioning of faulty components. The experiment shows that the fault diagnosis method can effectively achieve to locate faulty components.
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