Journal
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
Volume 87, Issue -, Pages 294-306Publisher
ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD
DOI: 10.1016/j.ymssp.2016.10.027
Keywords
Adaptive drift; Closed skew normal distribution; Remaining useful life prediction; Wiener process
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Funding
- National Natural Science Foundation of China (NSFC) [61473254, 61134001]
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Predicting the remaining useful life for operational devices plays a critical role in prognostics and health management. As the models based on the stochastic processes are widely used for characterizing the degradation trajectory, an adaptive skew-Wiener model, which is much more flexible than traditional stochastic process models, is proposed to model the degradation drift of industrial devices. To make full use of the prior knowledge and the historical information, an online filtering algorithm is proposed for state estimation, a two-stage algorithm is adopted to estimate unknown parameters as well. For remaining useful life prediction, a novel result is presented with an explicit form based on the closed skew normal distribution. Finally, sufficient Monte Carlo simulations and an application for ball bearings in rotating electrical machines are used to validate our approach.
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