Gearbox state identification and remaining useful life prediction based on MoG-HMM

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Journal of Vibration and Shock ›› 2013, Vol. 32 ›› Issue (15) : 20-25.

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Gearbox state identification and remaining useful life prediction based on MoG-HMM

Xinghui Zhang1 Jianshe Kang1 Cunming Gao2 Duanchao Cao1 Hongzhi Teng3

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Abstract

A new approach for state recognition and remaining useful life (RUL) prediction based on Mixture of Gaussians Hidden Markov Model (MoG-HMM) was presented. State number optimization method was established based on cluster validity measures. One can recognize the state through identifying the MoG-HMM that best fits the observations. Then, the RUL prediction method was presented at the recognition base. Finally, the data of gearbox’s full life cycle test was used to demonstrate the proposed methods. The results showed that the mean accuracy performance was 90.94%.

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Mixture of Gaussians Hidden Markov Model / Remaining useful life prediction / State recognition

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Xinghui Zhang Jianshe Kang Cunming Gao Duanchao Cao Hongzhi Teng. Gearbox state identification and remaining useful life prediction based on MoG-HMM[J]. Journal of Vibration and Shock, 2013, 32(15): 20-25