Bearing Fault Diagnosis Based on Wavelet Transform and ICA

摘要：

The key to fault diagnosis of rolling element bearing is how to find typical characteristic frequencies from low SNR mixed signals. Jointing Continuous Wavelet Transform (CWT) with Independent Component Analysis (ICA), this paper proposes a method to select wavelet scales with iso-interval frequency and analyze envelope spectrum of independent signal to diagnose the fault of rolling element bearing. Finally, the effectiveness of this method has been verified by practical signal of rolling element bearing.

关键词： Wavelet transform Independent Component Analysis iso-interval frequency rolling element bearing

作者: Qiang Wu Qingbo He Fanrang Kong Yongbin Liu Peng Li

作者单位: Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, Hefei 230026, China

会议类型: 国际会议

会议名称: 2011 International Conference on Machanical Engineering,Materials and Energy(2011年机械工程、材料与能源国际会议 ICMEME 2011)

会议地点: 大连

会议语种:英文

页码: 672-675

在线出版日期: 2011-10-19（万方平台首次上网日期，不代表论文的发表时间）