一种基于单回路模糊仿真的自适应克里金方法,用于估计随时间变化的故障可能性

IF 3.6 3区 计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS International Journal of Fuzzy Systems Pub Date : 2024-08-16 DOI:10.1007/s40815-024-01745-9
Kaixuan Feng, Zhenzhou Lu, Yixin Lu, Pengfei He
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引用次数: 0

摘要

为了提高双环模糊仿真(DLFS)估算随时间变化的故障可能性(TDFP)的效率,本文提出了单环模糊仿真(SLFS)。在 SLFS 中,首先提出了 TDFP 的等效变换公式,然后将 TDFP 的估计转换为单环模糊仿真程序,其中模糊输入和时间参数在同一水平上采样。由于 SLFS 只需单环采样,因此与 DLFS 相比,所提方法的计算复杂度和成本都有所降低。随后,为了提高 SLFS 的性能,我们开发了一种基于单环克里金模型的 SLFS(ASLK-SLFS)。基于 SLFS 的候选采样池在同一水平上对模糊输入和时间参数进行采样,可以更高效地构建和更新单一克里金。为了进一步提高 ASLK-SLFS 的效率,我们还利用候选采样池缩减策略开发了一个改进版本。最后,通过三个例子来说明所提方法的优势。通过所提出的 ASLK-SLFS 方法,可以有效地评估具有模糊不确定性的时变结构的安全度。
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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A Single-Loop Fuzzy Simulation-Based Adaptive Kriging Method for Estimating Time-Dependent Failure Possibility

To improve the efficiency of the double-loop fuzzy simulation (DLFS) for estimating the time-dependent failure possibility (TDFP), a single-loop fuzzy simulation (SLFS) is proposed in this paper. In the SLFS, an equivalent transformation formula of TDFP is put forward for the first time, then the estimation of TDFP is transformed into a single-loop fuzzy simulation procedure where the fuzzy inputs and time parameter are sampled in the same level. As only single-loop sampling is needed in the SLFS, the computational complexity and cost of the proposed method are both reduced compared to the DLFS. Subsequently, a single-loop Kriging model based SLFS (ASLK-SLFS) is developed to enhance the performance of the SLFS. Based on the candidate sampling pool of SLFS to sample the fuzzy inputs and the time parameter in the same level, a single Kriging can be more efficiently constructed and updated. To further improve the efficiency of ASLK-SLFS, an improved version is then developed by using a candidate sampling pool reduction strategy. Finally, three examples are employed to illustrate the advantages of the proposed methods. Through the proposed ASLK-SLFS, the safety degree of the time-dependent structure with fuzzy uncertainty can be efficiently evaluated.

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来源期刊
International Journal of Fuzzy Systems
International Journal of Fuzzy Systems 工程技术-计算机:人工智能
CiteScore
7.80
自引率
9.30%
发文量
188
审稿时长
16 months
期刊介绍: The International Journal of Fuzzy Systems (IJFS) is an official journal of Taiwan Fuzzy Systems Association (TFSA) and is published semi-quarterly. IJFS will consider high quality papers that deal with the theory, design, and application of fuzzy systems, soft computing systems, grey systems, and extension theory systems ranging from hardware to software. Survey and expository submissions are also welcome.
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