Real-Time Estimation of System Reliability Integrating Sensor-Driven Prognostic Model with Modular Approach

Abstract:

Real-time reliability estimation is very significant for system operation safety, particularly in railway transportation system. This paper proposes a method, integrating sensor-driven prognostic model with modular approach, to accurate estimate system real-time reliability. Modular approach is utilized to divide system fault tree into independent subtrees (modulars), and solves system reliability using Binary Decision Diagrams and Bayesian Networks according to their characteristics. Sensor-driven prognostic models use in situ sensor data from system components to compute their failure density functions or reliability functions, and continuously update system reliability. The method for system reliability assessment presented in this paper, integrating sensor-driven prognostic model with modular approach can overcome static characteristics of reliability analysis, and better correspond to practical applications.

• Periodical: Applied Mechanics and Materials (Volumes 494-495)
• Pages: 989-992
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.494-495.989
• Online since: February 2014
• Authors: Yong Jian Tao*
• Keywords: Modular Approach, Prognostic Model, Real-Time Estimation, System Reliability

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