Journal
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
Volume 25, Issue 2, Pages 537-548Publisher
ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD
DOI: 10.1016/j.ymssp.2010.07.003
Keywords
Stochastic dynamical models; Distribution of remaining useful life; Kalman filtering; Expectation-maximization
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Funding
- Slovenian Research Agency [P2-0001, L2-2110]
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In this paper we present a statistical approach to estimating the time in which an operating gear will reach a critical stage. The approach relies on measured vibration signals. From these signals features are first extracted and then their evolution over time is predicted. This is done based on a dynamic model that relates hidden degradation phenomena to measured outputs. The Expectation-Maximization algorithm is used to estimate the parameters of the underlying state-space model on line. The time to reach the safety alarm threshold is determined by estimating the distribution of the remaining useful life using the estimated linear model. The results obtained on a pilot test bed are presented. (C) 2010 Elsevier Ltd. All rights reserved.
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