大连理工大学学报2019，Vol.59Issue(1)：35-44,10.DOI:10.7511/dllgxb201901006
基于MCKD和teager能量算子的滚动轴承复合故障诊断
Composite fault diagnosis of rolling bearing based on MCKD and teager energy operator
摘要
Abstract
Rolling bearing is one of the main parts of rotating machinery, but the complex and changeable working environment causes frequent failure and many kinds of composite fault.In order to solve this problem, a composite fault diagnosis method of rolling bearing based on improved maximum correlated kurtosis deconvolution (MCKD) and teager energy operator is proposed.In this method, particle swarm optimization (PSO) is used to optimize the MCKD parameters (Land M) of different types of faults, set up the deconvolution period corresponding to the fault type, calculate the MCKD algorithm with the maximum correlation kurtosis, and improve the filter coefficients.The improved MCKD algorithm reduces the noise interference to a great extent, and then use the teager energy operator to detect the transient impact of the signal, and analyze the teager energy spectrum to realize the composite fault diagnosis.Finally, the method is validated by using the bearing data of Case Western Reserve University and the bearing fault simulator, and the results show that it can effectively extract fault feature information from single and composite fault of rolling bearing and identify the fault type accurately.关键词
复合故障/最大相关峭度解卷积(MCKD)/能量算子/故障诊断Key words
composite fault/maximum correlated kurtosis deconvolution (MCKD)/energy operator/fault diagnosis分类
机械制造引用本文复制引用
齐咏生,刘飞,高学金,李永亭,刘利强..基于MCKD和teager能量算子的滚动轴承复合故障诊断[J].大连理工大学学报,2019,59(1):35-44,10.基金项目
国家自然科学基金资助项目(61763037,21466026) （61763037,21466026）
内蒙古自治区自然科学基金资助项目(2017MS0601) （2017MS0601）
