Bearing Fault Diagnosis Based on Adaptive Multi-period Differential Mean
To address the problem that the features of bearing in the instantaneous angular speed(IAS)signal are weak,an adaptive multi-period differential mean(AMPDM)tool is proposed.Firstly,based on the advan-tages of the differential tool without amplitude interference and the accumulative characteristic of multi-period,a multi-period differential mean tool is peoposed to enhence the features related to the faulty bearing in the IAS signal to suppress the interference components,such as the encoder installation error,IAS estimation error and measurem ent noise,etc.Secondly,an improved diagnosis feature(IDF)indicator is proposed to evaluate the richness of fault information contained in the enhanced signal under different period number K conditions,and an optimal Kop corresponding to the maximum IDF is determined.Finally,the envelope order spectrum analysis is used to reveal the features related to the faulty bearing.Simulation and experimental results show that the AMPDM can effectively enhance bearing fault features in the IAS signal,and compared with multipoint optimal minimum entropy deconvolution adjusted,cepstrum pre-whitening and cyclic spectral correlation,the advan-tages of the AMPDM are verified.
bearing faultinstantaneous angular speedencoder signalmulti-period differential mean
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