STUDY OF BEARINGS FAULT DIAGNOSIS BASED ON GARCH MODEL

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Journal of Vibration and Shock ›› 2010, Vol. 29 ›› Issue (5) : 11-15.

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STUDY OF BEARINGS FAULT DIAGNOSIS BASED ON GARCH MODEL

Tao Xin-min1;Xu Jing2;Yang Li-biao1;Liu Yu1

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Abstract

In bearings fault detection application, to solve the problems of difficultly describing signal characteristics using auto-regressive(AR) models due to the signal’s non-stationary time series, a novel one-class diagnosis model using Multi-class Support Vector Machines based on Generalized Autoregressive Conditional Heteroscedasticity (GARCH) model is presented in this paper. The GARCH model is employed to describe the different bearings vibration signals, the parameters of the generated different models is used as the signal’ diagnosis characteristics and consequently the classifier based on MSVM is established. The experiments show that the proposed approach can efficiently overcome the drawback of conventional methods based on AR’ parameters. The proposed diagnosis scheme is compared against the conventional methods based on the AR model’s parameters and the other modified methods based on AR model as the diagnosis feature in the experiments. The results illustrate effectiveness of the investigated techniques with some concluding remarks in terms of diagnosis times and diagnosis rate.

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Fault Diagnosis / GARCH model / Multi-Class Support Vector Machine

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Tao Xin-min;Xu Jing;Yang Li-biao;Liu Yu. STUDY OF BEARINGS FAULT DIAGNOSIS BASED ON GARCH MODEL [J]. Journal of Vibration and Shock, 2010, 29(5): 11-15