Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/30899
Title: A Bayesian approach to condition monitoring with imperfect inspections
Authors: Ye, Z 
Chen, N
Tsui, KL
Keywords: Heterogeneous degradation rates
Measurement errors
Recursive filtering
Wiener process
Issue Date: 2015
Publisher: John Wiley and Sons Ltd
Source: Quality and reliability engineering international, 2015, v. 30, no. 4, p. 216-225 How to cite?
Journal: Quality and Reliability Engineering International 
Abstract: Degradation is a common phenomenon for many products. Because of a variety of reasons, the degradation rates of units from the same population are often heterogeneous. In addition, when the degradation process is monitored using dedicated sensors, the measurements are often inaccurate because of various noisy factors. To account for the heterogeneous degradation rate and the non-negligible measurement errors, we model the degradation observations using a random-effects Wiener process with measurement errors. Under the model, direct estimation of current degradation and prediction of future degradation are difficult. We thus develop a filtering algorithm that recursively estimates the joint distribution of the degradation rate and the current degradation levels. Based on the estimates, the distribution of the remaining useful life can be timely predicted. Our method is both computational efficient and storage efficient. Its effectiveness is demonstrated through simulation and real data.
URI: http://hdl.handle.net/10397/30899
ISSN: 1000-6753
DOI: 10.1002/qre.1609
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