高阶累积量自适应滤波在列车轴承故障诊断中的应用  

Adaptive Filter Based on Third-Order Cumulants in Fault Diagnosis of Rolling Bearing

作　　者：尚万峰[1] 关惠玲[1] 韩捷[1] 

机构地区：[1]郑州大学机械工程学院,河南郑州450002

出　　处：《中国工程机械学报》2004年第4期464-468,共5页Chinese Journal of Construction Machinery

摘　　要：论述了基于三阶累积量的递推最小二乘自适应算法(CDRLS)和基于累积量的指数遗忘窗的最小均方误差自适应算法(CDEFWLMS).通过对机车滚动轴承的保持架断裂典型故障信号的分析得出高阶统计量自适应算法具有良好的降噪性,CDEFWLMS 算法比 CDRLS 算法处理后的幅值更突出.讨论了用模糊 C 均值(FCM)算法聚类 CDEFWLMS 算法和 CDRLS 算法滤波后的信号频谱,得出经 CDEFWLMS 算法处理的故障隶属度要比CDRLS 算法较大,从而进一步验证了高阶累积量自适应算法在实际故障诊断和检测中有着良好的应用特性.Both adaptive CDRLS filter based third-order cumulants and adaptive CDEFWLMS filter based third-order cumulants apply to fault of diagnosis of rolling bearing.Analyse these typical faults of the locomo- tive freight car roller bearing such as bearing cage broken,bearing ball wearing,by which the result is that adaptive fliter based third-order cumulants has nice qualities,and CDEFWLMS filter is more effective than CDRLS filter in practice,and peak value in spectrum of the former is more sharp and apparent then the latter. Discuses clustering these signals processed by CDEFWLMS filter and CDRLS filter by means of FCM.The conclusion is data degree of membership of the former processing is higter than the latter.Further more,it val- idates apative filter based third-order cumulants in the field of fault diagnosis and monitoring.

关 键 词：高阶累积量 自适应滤波 故障诊断 模糊C均值算法 

分 类 号：TN911.7[电子电信—通信与信息系统] TH133.3[电子电信—信息与通信工程]