Affiliation:
1. State Key Laboratory of Mechanical Transmission Chongqing University Chongqing P.R. China
2. Center for System Reliability and Safety University of Electronic Science and Technology of China Chengdu Sichuan P.R. China
Abstract
AbstractThis paper proposes an active learning Kriging (ALK) based reliability analysis method for a multi‐output structural system by using a multiple response Gaussian process (MRGP) model. Firstly, various failure modes, including their interactions, are involved in a multi‐output structural system. The MRGP model is used to construct the surrogate model directly because it can efficiently characterize the correlation between different failure modes. The particle swarm optimization (PSO) algorithm is integrated into the MRGP model to optimize the hyperparameter. Secondly, similar to ALK‐based reliability method, three improved functions for these common learning functions (e.g., U‐function, EFF‐function, H‐function) are proposed, which consider the distance requirement between the iteration sample point and training samples. Finally, the cross‐validation methodology is employed as the stopping criterion and several numerical examples are provided to illustrate the effectiveness.
Funder
National Natural Science Foundation of China
Chinese Universities Scientific Fund
National Key Research and Development Program of China
Subject
Management Science and Operations Research,Safety, Risk, Reliability and Quality
Cited by
5 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献