Hybrid System Fault Diagnosis Method Based on Noise Variance Adaptive Correction

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Journal of Vibration and Shock ›› 2016, Vol. 35 ›› Issue (8) : 14-20.

Wang Qiang1,2 Liu Yong-bao1,2, He Xing1,2 ,Liu Shu-yong1

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Abstract

For hybrid system fault diagnosis problem in noise statistics properties time-varying, this paper proposed a multimodal fault diagnosis method based on noise variance adaptive relevant correction. First of all, within the framework of particle filter, hybrid system fault diagnosis is modeled as optimal state estimation and tracking problem, and real-time observation information and each modal prior transition probability is used to estimate the optimal fault mode. The estimating results are modeled separately for incoming analysis. Second, the noise variance adaptive online detection mechanism is built based on the correlation between smoothing estimation and the observation information, and updates the modal noise variance adaptively, which effectively overcomes the filter shift problem results from the time-varying noise statistical properties. The proposed method improves the robustness effectively. Finally, the experiments of three kinds failure modes show that the proposed method is efficient and robust.

Key words

Hybrid system / Fault detection / Particle filter / Noise statistical properties / Adaptive filter

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Wang Qiang1,2 Liu Yong-bao1,2, He Xing1,2,Liu Shu-yong1. Hybrid System Fault Diagnosis Method Based on Noise Variance Adaptive Correction[J]. Journal of Vibration and Shock, 2016, 35(8): 14-20

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