Fault diagnosis of rolling bearing based on improved time-varying Autoregressive Model

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Journal of Vibration and Shock ›› 2011, Vol. 30 ›› Issue (12) : 74-77,1.

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Fault diagnosis of rolling bearing based on improved time-varying Autoregressive Model

Lu Yu-hua; Wang Zhong-sheng; Jiang Hong-kai

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Abstract

An improved Time-Varying Autoregressive model is established for rolling bearing fault diagnosis based on combination of forward and backward estimation. By adopting time-varying forgetting factor, mean squared error based on forward and backward estimation error is defined and partial derivative is taken with respect to weighting coefficients of basis functions to obtain its calculation formula. Then, recursion formula of the weighting coefficients is derived using Recursive Least Squares (RLS). Time-frequency analysis on analog and experimental signal of faulty inner ring is conducted using improved and unimproved model. The result shows that, the improved model can overcome the unavailability of frequency estimation at the initial time, has more accuracy in temporal and frequency estimation, and better anti-noise performance. So the improved model can withdraw fault feature frequency of rolling bearing more efficiently.

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improved time-varying autoregressive model / recursive least squares / rolling bearing / fault diagnosis

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Lu Yu-hua;Wang Zhong-sheng;Jiang Hong-kai. Fault diagnosis of rolling bearing based on improved time-varying Autoregressive Model[J]. Journal of Vibration and Shock, 2011, 30(12): 74-77,1