Bearings Fault Diagnosis Based on Multiwavelet Energy Statistics Measure

摘要：

In order to solve the problems of correctly identifying incipient fault for bearings and improve classification ability, the new scheme for bearing fault diagnosis based on multiwavelet energy statistics was proposed. The signal energy spectrum in multiwavelet domain was used as fault diagnosis characteristics. With the distance evaluation technique, the optimal features sub-filed were obtained. The optimal features were input into the SVM to identify the different fault cases. The Receiver Operating Characteristic curve (ROC) was applied to evaluate the effect of different multiwavelets preprocess methods. Finally, the experimental results show that the proposed methods can more efficiently opposes the characters of different fault cases and diagnose bearings faults with the appropriate preprocess methods.

关键词： fault diagnosis multiwavelet wavelet energy statistics multiwavelet preprocess

作者: Jing XU Jing SHAN Qiu-jie ZHAN Ping JIANG

作者单位: Department of Mathematics and Mechanics, Heilongjiang Institute of Science and Technology,Harbin 150027

会议类型: 国际会议

会议名称: The Third International Conference on Modelling and Simulation(第三届国际建模、计算、仿真、优化及其应用学术会议 ICMS 2010)

会议地点: 无锡

会议语种:英文

页码: 446-449

在线出版日期: 2010-06-04（万方平台首次上网日期，不代表论文的发表时间）