A Model for Real Time Remaining Useful Life Prediction of Gear Based on Abrupt Change Detection

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Journal of Vibration and Shock ›› 2017, Vol. 36 ›› Issue (21) : 173-184.

SHI Hui1 ZENG Jianchao1,2

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Abstract

In order to solve the gear contact fatigue remaining useful life in the degradation process is difficult to accurately predict problems, a new method of real-time gear contact fatigue remaining useful life prediction is put forward that is a kind of integrated studies of abrupt change detection and remaining life prediction. Firstly, the state-space modelling for predicting degradation states of gear wear was established by using the real time monitoring vibration information received to update the model parameters. Using Kalman forward filtering and smoothing algorithm combined with parameter estimation of expectation–maximization algorithm, the prediction model was modified to change the filtering effect according to the life information of abrupt change detection provided. Using real-time monitoring data of the contact fatigue life of gear test rig to verify this model, the results show that a revised prediction model using abrupt point information can be faster to dynamic tracking system, improve the accuracy of gear degradation state and the real-time remaining useful life prediction.

Key words

Remaining useful life prediction / State-space models / Kalman filtering / Abrupt change detection / Model correction

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SHI Hui1 ZENG Jianchao1,2. A Model for Real Time Remaining Useful Life Prediction of Gear Based on Abrupt Change Detection[J]. Journal of Vibration and Shock, 2017, 36(21): 173-184

References

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