摘要
环境噪声处理不当或者传感器数目少于故障数目都可能导致基于源分离的复合故障诊断失败,针对此问题,提出了基于改进样板去噪源分离的诊断方法并用于轴承复合故障诊断。该方法首先对数据进行移动独立分量分析,然后将得到的独立成分作为输入样板进行样板去噪源分离。轴承复合故障的仿真和实验数据分析证明,该方法能够在未知噪声环境下完成传感器数目少于故障数目的欠定源分离,该方法对轴承复合故障诊断是有效的。
Processing noise improperly or the number of sensors less than the numner of faults may lead to failure of multi-fault diagnosis based on source separation.Improved template denoising source separation was proposed and used to diagnose multi-fault of bearings.Shift independent component analysis was carried out first and the independent components obtained were used as templates to the template denoising source separation algorithm.The proposed method can separate source signals through underdetermined source under reverberant environments and diagnose multi-fault of bearings.The effectiveness was verified by both simulated and experimental anlysis.
出处
《中国机械工程》
EI
CAS
CSCD
北大核心
2011年第17期2080-2084,共5页
China Mechanical Engineering
基金
国家自然科学基金资助项目(51075330
50975231)
关键词
复合故障
改进样板去噪源分离
轴承
欠定源分离
multi-fault
improved template denoising source separation
bearing
underdetermined source separation
