电测与仪表2017，Vol.54Issue(11)：1-7,7.
基于交叉小波变换和主元分析的电力电子电路故障特征提取
Fault feature extraction of power electronics circuits based on cross-wavelet transform and principle component analysis
摘要
Abstract
Aiming at drawbacks of current methods for power electronics circuits feature extraction.there is not enough accuracy and not obvious classification, and the process of feature extraction is easily affected by noise.Firstly, the faulty signal of circuit information feature is analyzed and extracted by cross-wavelet transform.Then, the initial feature matrix is obtained representing cross-wavelet spectrum.Finally, principle component analysis is applied for reducing the dimension of initial feature matrix and those which redundant information are eliminated.The back propagation (BP) neural network classifiers are utilized for fault diagnosis simulation test.The results show that the fault detection accuracy is up to 98.2%.Simulation results demonstrate the accuracy of the proposed method.关键词
电力电子电路特征提取/交叉小波/主元分析Key words
power electronics circuits/feature extraction/cross-wavelet/principle component analysis分类
信息技术与安全科学引用本文复制引用
况璟,何怡刚,邓芳明,施天成..基于交叉小波变换和主元分析的电力电子电路故障特征提取[J].电测与仪表,2017,54(11):1-7,7.基金项目
国家自然科学基金资助项目(51577046) （51577046）
国家自然科学基金重点项目(51637004) （51637004）
国家重点研发计划"重大科学仪器设备开发"项目(2016YFF0102200) （2016YFF0102200）
