用统计数据估计的三角多模糊集分析不同系统的可靠性

E. El-Ghamry, M. El-Halawany, M. Shokry
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引用次数: 1

摘要

本文首先简要介绍了多模糊集及其算术运算,然后提出了用多模糊集方法对不同类型的不可修复模糊系统进行可靠性分析的思想,包括串联、并联、串并联和并联串联系统。由于对故障原因和后果的了解通常具有较大的不确定性,因此可以用三角多模糊集来表示各部件的可靠性。每个多模糊集使用置信区间的概念进行估计,该置信区间是基于从每个组成部分的随机样本中获取的统计数据计算出来的。通过数值算例验证了多模糊集在不同结构工程系统中的适用性,并利用MAPLE软件进行了计算。
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Reliability analysis of different systems using triangular multi-fuzzy sets estimated by statistical data
In this paper, the multi-fuzzy sets and its arithmetic operations are first introduced briefly then we describe an idea of using multi-fuzzy sets approach to reliability analysis of different types of unrepairable fuzzy systems as series, parallel, series-parallel and parallel-series systems consist of independent components. The knowledge about causes and effects of failures is usually described with large uncertainty content so the reliability of each component can be represented by triangular multi-fuzzy set. Each multi-fuzzy set is estimated by using the concept of confidence interval that calculated based on statistical data taken from random samples of each component. A numerical example is given to demonstrate the applicability of the multi-fuzzy sets in different structural engineering systems and the results were drawn by using MAPLE software program.
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