A Metamodeling Approach using Bayesian Network for Reliability Estimation of Dynamic Systems (一种基于贝叶斯网络的动态系统可靠性评估代理模型建立方法)

Xiaoling Zhang
received her Ph. D. degree in Reliability Engineering from University of Electronic Science and Technology of China. She was a pre-doctoral visiting fellow in the department of mechanical and aerospace engineering, Rutgers University, from 2009 to 2011. She is currently an associated professor of the School of Mechanical Engineering, University of Electronic Science and Technology of China. She ha...read more



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Abstract: At the early design stages, it is difficult to have accurate models of complex systems, especially dynamic systems. In this talk, an information fusion framework based on Bayesian network is proposed for building surrogate models for dynamic systems. Within this framework, considering the uncertainty of system input, the method for fusing multi-level system data, objective and subjective information with Bayesian network will be presented. The surrogate model and simulation method are then used to estimate time-dependent reliability. The efficiency and accuracy of the proposed method are testified by an analytical function and the case study of the Lifting Gear Transmission System of Mining Excavator. Speaker Bio: Xiaoling Zhang received her Ph. D. degree in Reliability Engineering from University of Electronic Science and Technology of China. She was a pre-doctoral visiting fellow in the department of mechanical and aerospace engineering, Rutgers University, from 2009 to 2011. She is currently an associated professor of the School of Mechanical Engineering, University of Electronic Science and Technology of China. She has published more than 10 research papers in the fields of reliability engineering and optimization design. Her current research interests include reliability analysis, reliability based design and multidisciplinary design optimization.


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