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State estimation of discrete event systems for RUL prediction issue

Author

Listed:
  • Rabah Ammour
  • Edouard Leclercq
  • Eric Sanlaville
  • Dimitri Lefebvre

Abstract

This paper concerns Remaining Useful Life (RUL) estimation of discrete event systems. For that purpose, physics-based models with partially observed stochastic Petri nets are used to represent the system and its sensors. The advantage of the proposed modelling approach is to provide a realistic representation of the system, including the interaction between the normal behaviours and the failure processes. From the proposed modelling and collected measurements, timed trajectories, which are consistent with the observations, are obtained. Based on the event dates, our approach consists in evaluating the probabilities of the consistent behaviours using probabilistic models. State estimation is obtained as a consequence. The most probable future degradations, from the current state, are then considered and a method for fault prognosis is presented. Finally, the prognosis result is used to estimate the RUL as a time interval. A case study is proposed to show the applicability of the proposed method.

Suggested Citation

  • Rabah Ammour & Edouard Leclercq & Eric Sanlaville & Dimitri Lefebvre, 2017. "State estimation of discrete event systems for RUL prediction issue," International Journal of Production Research, Taylor & Francis Journals, vol. 55(23), pages 7040-7057, December.
    • Handle: RePEc:taf:tprsxx:v:55:y:2017:i:23:p:7040-7057
    DOI: 10.1080/00207543.2017.1346835
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    Cited by:

    1. Chunhui Guo & Chuan Lyu & Jiayu Chen & Dong Zhou, 2018. "A multi-event combination maintenance model based on event correlation," PLOS ONE, Public Library of Science, vol. 13(11), pages 1-24, November.

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