370 – Facets of Risk Assessment Based on Complex Data Structures with Applications in the Biomedical and Engineering Settings
Failure Prediction from Condition Monitoring of Complex Systems
Bo Henry Lindqvist
Norwegian University of Science and Technology
Gunnhild Hardersen Presthus
Norwegian University of Science and Technology
We consider a technical system subjected to condition monitoring by a marker process Y(t). Failure of the system is closely connected to the event that the process Y(t) crosses a certain critical threshold. The monitored process Y(t) depends probabilistically on the state of a latent process S(t), representing the underlying technical condition of the system. The goal is to, based on the observation of the process Y(t), estimate the distribution of the first passage time of Y(t) of the critical threshold. The process Y(t) is modeled as a piecewise Wiener process with change points determined by the latent process S(t). A Bayesian approach involving Markov Chain Monte Carlo simulations is used for estimation.