Bearing fault diagnosis based on Shannon entropy and wavelet package decomposition

摘要：

　　A new feature extraction method based on WPD and Entropy is proposed in this paper.Firstly, WPD is utilized to decompose the signal into different frequency bands to obtain different frequency sub-signal.Secondly, root-mean-squire (RMS) value, kurtosis (K) and peak factor (PF)parameters are extracted from each sub-signal to obtain the fault feature vector.Thirdly the Entropy of each feature vector is calculated to realize the bearing fault diagnosis.Finally,experimental results indicate that the bearing fault diagnosis method proposed in this paper is effective.

关键词： bearing entropy wavelet package decomposition

作者: Hong Mei Liu Chen Lu Ji Chang Zhang

作者单位: School of Reliability and Systems Engineering, Beihang University, Beijing 100191, China

会议类型: 国际会议

会议名称: the International Conference Vibroengineering-2014

会议地点: 贵阳

会议语种:英文

页码: 223-228

在线出版日期: 2014-11-07（万方平台首次上网日期，不代表论文的发表时间）