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Fault Detection of a Proposed Three-Level Inverter Based on a Weighted Kernel Principal Component Analysis
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  • Journal title : Journal of Power Electronics
  • Volume 16, Issue 1,  2016, pp.182-189
  • Publisher : The Korean Institute of Power Electronics
  • DOI : 10.6113/JPE.2016.16.1.182
 Title & Authors
Fault Detection of a Proposed Three-Level Inverter Based on a Weighted Kernel Principal Component Analysis
Lin, Mao; Li, Ying-Hui; Qu, Liang; Wu, Chen; Yuan, Guo-Qiang;
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 Abstract
Fault detection is the research focus and priority in this study to ensure the high reliability of a proposed three-level inverter. Kernel principal component analysis (KPCA) has been widely used for feature extraction because of its simplicity. However, highlighting useful information that may be hidden under retained KPCs remains a problem. A weighted KPCA is proposed to overcome this shortcoming. Variable contribution plots are constructed to evaluate the importance of each KPC on the basis of sensitivity analysis theory. Then, different weighting values of KPCs are set to highlight the useful information. The weighted statistics are evaluated comprehensively by using the improved feature eigenvectors. The effectiveness of the proposed method is validated. The diagnosis results of the inverter indicate that the proposed method is superior to conventional KPCA.
 Keywords
Fault detection;Kernel principal component analysis (KPCA);Sensitivity analysis;Three-level inverter;
 Language
English
 Cited by
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