Diagnosis of Rolling Elements Bearing Based on Inverse Autoregressive Filter
Diagnosis of rolling elements bearing plays an important role on the running and maintenance of mechanical equipments. To enhance the feature of fault and to further diagnose the status of bearings with a small fault size so as to realize the early recognition, the method of inverse filter based on Autoregressive model is presented in this paper, and the corresponding criterion of order selection is also discussed. Analysis of simulation signals and real data show that this method could enhance feature of impulse signal. Meanwhile, it is also found that for small size fault, the root mean square feature is more effective than kurtosis value, which is considered very useful for early diagnosis of rolling elements bearings.
F. Chu, H. Ouyang, V. Silberschmidt, L. Garibaldi, C.Surace, W.M. Ostachowicz and D. Jiang
L. Garibaldi et al., "Diagnosis of Rolling Elements Bearing Based on Inverse Autoregressive Filter", Key Engineering Materials, Vols. 413-414, pp. 635-642, 2009