Modelling wear degradation in cylinder liners
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Date
2016
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Abstract
We present and discuss a stochastic model describing the wear process of cylinder
liners in a marine diesel engine. The model is based on a stochastic differential
equation and Bayesian inference is illustrated. Corrosive action and measurement
error, both quite negligible, are modeled with a Wiener process whereas a jump
process is used to describe the contribution of soot particles to the wear process.
The model can be used to forecast the wear process and, consequently, plan condition
based maintenance activities. In the paper, we provide a critical illustration
of the mathematical and computational aspects of the model. We propose a strategy
that, implemented for simulated and real data, allows for stable parameter
estimation and forecasts.
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Keywords
Bayesian inference, stochastic differential equations, Markov chain Monte Carlo, condition based maintenance