Modeling multi-state equipment degradation with non-homogeneous continuous-time hidden semi-markov process

Ramin Moghaddass, Ming J. Zuo, Xiaomin Zhao

Research output: Chapter in Book/Report/Conference proceedingChapter

6 Scopus citations

Abstract

The multi-state reliability analysis has received great attention recently in the domain of reliability and maintenance, specifically for mechanical equipment operating under stress, load, and fatigue conditions. The overall performance of this type of mechanical equipment deteriorates over time, which may result in multi-state health conditions. This deterioration can be represented by a continuous-time degradation process with multiple discrete states. In reality, due to technical problems, directly observing the actual health condition of the equipment may not be possible. In such cases, condition monitoring information may be useful to estimate the actual health condition of the equipment. In this chapter, the authors describe the application of a general stochastic process to multi-state equipment modeling. Also, an unsupervised learning method is presented to estimate the parameters of this stochastic model from condition monitoring data.

Original languageEnglish (US)
Title of host publicationDiagnostics and Prognostics of Engineering Systems
Subtitle of host publicationMethods and Techniques
PublisherIGI Global
Pages151-181
Number of pages31
ISBN (Print)9781466620957
DOIs
StatePublished - Dec 1 2012
Externally publishedYes

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ASJC Scopus subject areas

  • Engineering(all)

Cite this

Moghaddass, R., Zuo, M. J., & Zhao, X. (2012). Modeling multi-state equipment degradation with non-homogeneous continuous-time hidden semi-markov process. In Diagnostics and Prognostics of Engineering Systems: Methods and Techniques (pp. 151-181). IGI Global. https://doi.org/10.4018/978-1-4666-2095-7.ch008