Hierarchical Bayesian modeling for uncertainty quantification and reliability updating using data
Papers|更新时间:2025-04-21
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Hierarchical Bayesian modeling for uncertainty quantification and reliability updating using data
基于数据的分层贝叶斯建模:不确定性量化与可靠性更新
“In the field of engineering systems, a hierarchical Bayesian modeling framework is introduced to quantify uncertainty and update reliability. Expert established the HBM system, which provides solutions to solve multi-source uncertainty problems in both static and dynamic contexts, laying a foundation for the construction of structural health monitoring systems.”
Journal of Reliability Science and EngineeringIssue 2, Pages: 1-16(2025)
作者机构:
State Key Laboratory of Reliability and Intelligence of Electrical Equipment, School of Mechanical Engineering, Hebei University of Technology, 300401Tianjin, People's Republic of China
Department of Mechanical Engineering, University of Thessaly, 38334Volos, Greece
作者简介:
[
"Xinyu Jia is an associate professor of Mechanical Engineering at Hebei University of Technology in Tianjin, China. His research interests include uncertainty quantification and reliability analysis of complex equipment, dynamic design and control of industrial robots, structural health monitoring, and digital twins."
]
[
"Weinan Hou received the Bachelor of Engineering degree in Mechanical Design, Manufacturing, and Automation from Hebei University of Technology in 2023. He is currently pursuing the M.Sc. degree in Mechanical Engineering with Hebei University of Technology. His research interests include Bayesian model updating and reliability analysis."
]
[
"Costas Papadimitriou is a professor of Mechanical Engineering at the University of Thessaly in Greece. His current research interests include uncertainty quantification, Bayesian inference, structural dynamics, structural health monitoring and reliability."
]