Adaptive condition-based maintenance decision framework for deteriorating systems operating under variable environment and uncertain condition monitoring

作者：Khac Tuan Huynh^*; Barros Anne; Berenguer Christophe

来源：Proceedings of the Institution of Mechanical Engineers - Part O: Journal of Risk and Reliability , 2012, 226(O6): 602-623.

DOI：10.1177/1748006X12465718

• Adaptive maintenance decision
• diagnostic covariate
• environmental covariate
• fatigue crack growth
• indirect condition monitoring
• maintenance cost model
• particle filter

The present article deals with the efficient use of different types of monitoring information in optimizing condition-based maintenance decision making for a deteriorating system operating under variable environment. The degradation phenomenon of a system is the fatigue crack growth that is modeled by a physics-based stochastic process. The environment process is assumed to be modeled by a time-homogenous Markov chain with finite state space. We suppose that the environmental condition is observed perfectly, while the crack depth can be assessed imperfectly through a non-destructive ultrasonic technique. As such, two kinds of indirect information are available on the system at each inspection time: environmental covariate and diagnostic covariate. Based on this set of information, two condition-based maintenance strategies adaptive to environmental conditions are developed. In the first one, the adaptation scheme is time-based, while in the second, it is condition-based. These maintenance strategies are compared one with another and to a classical non-adaptive one to point out the performances of each adaptation scheme and hence the appreciation of using different information sources in maintenance decision making.

• 出版日期2012-12