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Reliability engineering & system safety v.160, 2017년, pp.21 - 36   SCI SCIE SCOPUS
본 등재정보는 저널의 등재정보를 참고하여 보여주는 베타서비스로 정확한 논문의 등재여부는 등재기관에 확인하시기 바랍니다.

System dynamic reliability assessment and failure prognostics

Liu, Jie (Chair on System Science and the Energetic Challenge, EDF Foundation, CentraleSupélec, Université ) ; Zio, Enrico (Paris-Saclay, Grande voie des Vignes, 92290 Chatenay-Malabry, France ) ;
  • 초록  

    Abstract Traditionally, equipment reliability assessment is based on failure data from a population of similar equipment, somewhat giving an average description of the reliability performance of an equipment, not capturing the specificity of the individual equipment. Monitored degradation data of the equipment can be used to specify its behavior, rendering dynamic the reliability assessment and the failure prognostics of the equipment, as shown in some recent literature. In this paper, dynamic reliability assessment and failure prognostics with noisy monitored data are developed for a system composed of dependent components. Parallel Monte Carlo simulation and recursive Bayesian method are integrated in the proposed modelling framework to assess the reliability and to predict the Remaining Useful Life (RUL) of the system. The main contribution of the paper is to propose a framework to estimate the degradation state of a system composed of dependent degradation components whose conditions are monitored (even without knowing the initial system degradation state) and to dynamically assess the system risk and RUL. As case study, a subsystem of the residual heat removal system of a nuclear power plant is considered. The results shows the significance of the proposed method for tailored reliability assessment and failure prognostics. Highlights A system composed of dependent components is considered for reliability assessment. Each component may follow a multi-state or continuous degradation process. Noisy monitored data related to system degradation is considered for update. Recursive Bayesian method and Monte Carlo simulation are combined in the framework. A case study considering a subsystem in nuclear power plant is carried out.


  • 주제어

    Dependent degradation .   Failure prognostics .   Monte Carlo simulation .   Multiple component .   Reliability assessment .   Recursive Bayesian method.  

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