Real-time high-fidelity reliability updating with equality information using adaptive Kriging
Real-time high-fidelity reliability updating with equality information using adaptive Kriging
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DOI：
10.1016/j.ress.2019.106735
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发表时间：
2020-03
期刊：
影响因子：
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通讯作者：
Zeyu Wang;A. Shafieezadeh
中科院分区：
文献类型：
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作者：
Zeyu Wang;A. Shafieezadeh
现有的等式信息可靠性更新方法通过引入辅助随机变量，将这一具有挑战性的问题转化为不等式问题。然而，在导出的条件概率中，信息和故障的联合事件通常非常罕见，因此，估计起来非常具有挑战性。此外，随着新信息的到来而更新可靠性需要重新评估联合事件的概率，这涉及对性能函数的大量调用。我们提出了一种新的方法，称为RUAK的可靠性更新解决这些限制。其中一个重要贡献是将失效和观测信息的罕见联合事件分解为两个概率相对较高的事件。此外，提出了一种基于Kriging的自适应可靠性分析方法，用于先验失效概率和信息条件概率的估计。这样，新的信息的可靠性更新进行了有效的克里格元模型，这显着提高了计算效率。四个例子的结果表明，使用RUAK的计算需求减少了两个数量级相比，国家的最先进的方法，同时实现更高的精度。这种方法有利于实时可靠性更新的各种应用程序，如健康监测和报警系统。
Current state-of-the-art methods for reliability updating with equality information transform this challenging problem into an inequality one by introducing an auxiliary random variable. However, the joint event of information and failure in the derived conditional probabilities is typically very rare, and therefore, very challenging to estimate. Moreover, updating the reliability as new information arrives requires reevaluation of the probability of the joint event, which involves large numbers of calls to performance functions. We address these limitations by proposing a new approach to reliability updating called RUAK. One of the important contributions is the decomposition of the rare joint event of the failure and observed information into two events both with relatively high probabilities. Moreover, an adaptive Kriging-based reliability analysis method is proposed for the estimation of the prior failure probability and the conditional probability of information. This way, reliability updating for new information is conducted using the efficient Kriging meta-model, which significantly enhances the computational efficiency. Results for four examples indicate that the computational demand using RUAK is decreased by two orders of magnitude compared to the state-of-the-art methods, while achieving higher accuracy. This approach facilitates real-time reliability updating for various applications such as health monitoring and warning systems.