| Affiliation: | 1. School of Mechanical and Electrical Engineering, University of Electronic Science and Technology of China, Chengdu, China;2. School of Mechanical and Electrical Engineering, University of Electronic Science and Technology of China, Chengdu, China
Center for System Reliability and Safety, University of Electronic Science and Technology of China, Chengdu, China;3. Center for System Reliability and Safety, University of Electronic Science and Technology of China, Chengdu, China |
| Abstract: | The Bayesian network (BN) is an efficient tool for probabilistic modeling and causal inference, and it has gained considerable attentions in the field of reliability assessment. The common cause failure (CCF) is simultaneous failure of multiple elements in a system under a common cause, and it is a common phenomenon in engineering systems with dependent elements. Several models and methods have been proposed for modeling and assessment of complex systems with CCF. In this paper, a new reliability assessment method is proposed for the systems suffering from CCF in a dynamic environment. The CCF among components is characterized by a BN, which allows for bidirectional reasoning. A proportional hazards model is applied to capture the dynamic working environment of components and then the reliability function of the system is obtained. The proposed method is validated through an illustrative example, and some comparative studies are also presented. |
