Power Quality Disturbance Recognition Using S-transforms and FCM-based Decision Tree

摘要：

This paper presents a new approach for recognizing nonstationary signals in power quality (PQ) disturbances. Meanwhile the new approach includes the most types of PQ disturbance, such as voltage sags, swells, interruptions, transients and harmonics. The new model mainly includes two steps. Firstly, Stransform is used to analyze power system disturbance signals, and two most distinguishing features are extracted. In this process based on these two features, 2D feature vectors are clustered using hierarchical Fuzzy C-means algorithm (FCM). Secondly, a binary decision tree is constructed from FCM cluster centers to automatic recognize disturbance patterns. Finally the simulation results show the validity and efficiency of the proposed model.

关键词： power quslity(PQ) power quslity(PQ) disturbance pattern recognition S-transform fuzzy C-means algrithm(FCM) decision tree

作者: Nantian Huang Dianguo Xu Xiaosheng Liu

作者单位: Department of Electrical Engineering,Harbin Institute of Technology,Harbin,China;College of Informat Department of Electrical Engineering,Harbin Institute of Technology,Harbin,China

会议类型: 国际会议

会议名称: 2009 IEEE International Conference on Intelligent Computing and Intelligent Systems(2009 IEEE 智能计算与智能系统国际会议)

会议地点: 上海

会议语种:英文

页码: 2761-2765

在线出版日期: 2009-11-20（万方平台首次上网日期，不代表论文的发表时间）