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Sensors 2017, 17(9), 2123; https://doi.org/10.3390/s17092123

Modeling of BN Lifetime Prediction of a System Based on Integrated Multi-Level Information

1
School of Reliability and Systems Engineering, Beihang University, Beijing 100191, China
2
Unmanned System Institute, Beihang University, Beijing 100191, China
3
Key Laboratory of Advanced Technology of Intelligent Unmanned Flight System of Ministry of Industry and Information Technology, Beihang University, Beijing 100191, China
*
Author to whom correspondence should be addressed.
Received: 11 August 2017 / Revised: 13 September 2017 / Accepted: 13 September 2017 / Published: 15 September 2017
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Abstract

Predicting system lifetime is important to ensure safe and reliable operation of products, which requires integrated modeling based on multi-level, multi-sensor information. However, lifetime characteristics of equipment in a system are different and failure mechanisms are inter-coupled, which leads to complex logical correlations and the lack of a uniform lifetime measure. Based on a Bayesian network (BN), a lifetime prediction method for systems that combine multi-level sensor information is proposed. The method considers the correlation between accidental failures and degradation failure mechanisms, and achieves system modeling and lifetime prediction under complex logic correlations. This method is applied in the lifetime prediction of a multi-level solar-powered unmanned system, and the predicted results can provide guidance for the improvement of system reliability and for the maintenance and protection of the system. View Full-Text
Keywords: multi-level system; lifetime prediction; Bayesian Networks; multi-sensor information integration; complex logical correlation multi-level system; lifetime prediction; Bayesian Networks; multi-sensor information integration; complex logical correlation
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Wang, J.; Wang, X.; Wang, L. Modeling of BN Lifetime Prediction of a System Based on Integrated Multi-Level Information. Sensors 2017, 17, 2123.

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