Adaptive support vector machine for time-variant failure probability function estimation

IF 9.4 1区 工程技术 Q1 ENGINEERING, INDUSTRIAL
Weiming Zheng, Xiukai Yuan, Xiya Bao, Yiwei Dong
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引用次数: 0

Abstract

Time variant reliability analysis introduces additional complexity due to the inclusion of time. When the time-variant failure probability function (TFPF) of the structure is of interest, it inherently involves sequential evaluations of the failure probabilities of series systems varied with time in discretized space, posing a challenge to reliability analysis. An efficient approach for the evaluation of the TFPF, called ‘Time-dependent Adaptive Support Vector Machine combined with Monte Carlo Simulation’ (TASVM-MCS), is presented to reduce the corresponding computational cost. Based on the samples from Monte Carlo simulation (MCS), an iterative strategy is proposed to actively extract the most valuable sample points from the sample pool and iteratively update the support vector machine (SVM) model. In particular, an active learning function is proposed to take into account the diversity of samples and time simultaneously. In this way, the built SVM will be more suitable for the evaluation of TFPF other than a point-wise failure probability. The proposed TASVM-MCS method is relatively less sensitive to the dimensionality of the input variables, making it a powerful and promising approach for time-variant reliability computations. Four representative examples are given to demonstrate the significant effectiveness and efficiency of the proposed method.
用于估算时变故障概率函数的自适应支持向量机
时变可靠性分析由于包含时间而带来了额外的复杂性。当结构的时变失效概率函数(TFPF)受到关注时,它本身就涉及在离散空间中对随时间变化的系列系统的失效概率进行连续评估,这给可靠性分析带来了挑战。为了降低相应的计算成本,本文提出了一种高效的 TFPF 评估方法,即 "与时间相关的自适应支持向量机与蒙特卡罗模拟相结合"(TASVM-MCS)。基于蒙特卡罗模拟(MCS)的样本,提出了一种迭代策略,从样本池中主动提取最有价值的样本点,并迭代更新支持向量机(SVM)模型。特别是,提出了一种主动学习函数,以同时考虑样本和时间的多样性。这样,建立的 SVM 将比按点计算的故障概率更适合用于 TFPF 的评估。所提出的 TASVM-MCS 方法对输入变量的维度敏感性相对较低,因此是一种功能强大、前景广阔的时变可靠性计算方法。本文给出了四个具有代表性的例子,以证明所提方法的显著效果和效率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Reliability Engineering & System Safety
Reliability Engineering & System Safety 管理科学-工程:工业
CiteScore
15.20
自引率
39.50%
发文量
621
审稿时长
67 days
期刊介绍: Elsevier publishes Reliability Engineering & System Safety in association with the European Safety and Reliability Association and the Safety Engineering and Risk Analysis Division. The international journal is devoted to developing and applying methods to enhance the safety and reliability of complex technological systems, like nuclear power plants, chemical plants, hazardous waste facilities, space systems, offshore and maritime systems, transportation systems, constructed infrastructure, and manufacturing plants. The journal normally publishes only articles that involve the analysis of substantive problems related to the reliability of complex systems or present techniques and/or theoretical results that have a discernable relationship to the solution of such problems. An important aim is to balance academic material and practical applications.
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