Hidden Markov Models for diagnostics and prognostics of systems under multiple deterioration modes
Résumé
Multi-state systems have recently attracted a great deal of interest with regards to reliability and maintenance. Since most mechanical equipment operates under some sorts of stress or load, it tends to degrade over time, thus possibly resulting in discrete degradation states (damage degrees), ranging from perfect functioning to complete failure. Over recent years, Hidden Markov Models (HMMs) have been applied to model these discrete degradation states for diagnostic and prognostic purposes. However, most of the reported researches on HMMs for multi-state equipment in the literature consider only one degradation mechanism of degradation processes. The present paper proposes a novel model called multi-branch HMM (MB-HMM) to deal with deterioration processes modeling under multiple competing modes. To illustrate the proposed approach, a numerical study is given.
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