Fault Diagnosis of Power Quality

摘要：

The proposed method in this paper indicates two issues, selection of discriminative features and classifies event classes with minimum error. Wavelets features (WF) of power quality (PQ) events are extracted using wavelet transform (WT) and fuzzy classifiers classify events using these features. The captured signals are often corrupted by noise; the non-linear and non-stationary behaviors of PQ events make the detection and classification tasks more cumbersome. Performance comparison of the proposed method is made with three other fuzzy classifiers using different wavelets and superiority is verified. In the proposed approach of event classification, fuzzy product aggregation reasoning rule based method has been used.

关键词： Fault diagnosis Fuzzy systems Power quality Fuzzy classifiers

作者: Ou Yang-Ian

作者单位: School of Traffic and Transportation Engineering, Changsha University of Science & Technology,Changsha, 410004

会议类型: 国际会议

会议名称: 4th International Conference on Measuring Technology and Mechatronics Automation(第四届检测技术与机电自动化国际会议 ICMTMA 2012)

会议地点: 三亚

会议语种:英文

页码: 870-873

在线出版日期: 2012-01-06（万方平台首次上网日期，不代表论文的发表时间）