基于统一系数的多值模糊因果图推理算法

Xinyuan Liang
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引用次数: 11

摘要

单值模糊因果图的推理算法不能直接应用于多值模糊因果图。因此,有必要对MFCD的推理算法进行研究。本文首先讨论了MFCD的推理问题,提出了解决该问题的准则,并提出了一种事件状态模糊概率归一化方法对数据进行预处理。其次,提出了一种基于统一系数的MFCD推理算法来处理MFCD的推理。最后,以某核电站蒸汽发生器故障诊断为例,验证了该推理算法的有效性,结果与实际吻合。研究表明,MFCD推理算法有效地解决了MFCD故障分析推理问题,推理过程严谨,结果与实际吻合。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Reasoning Algorithm of Multi-Value Fuzzy Causality Diagram Based on Unitizing Coefficient
Reasoning algorithm of single-value fuzzy causality diagram (SFCD) cannot directly apply to multi-value fuzzy causality diagram (MFCD). So it is necessary to study reasoning algorithm of MFCD. Firstly, with the discussing of reasoning problem of MFCD in this paper, a guideline to solve the problem is introduced, and a normalization method of fuzzy probability of event state is proposed to preprocess data. Secondly, a reasoning algorithm of MFCD based on unitizing coefficient is proposed to deal with the reasoning of MFCD. Lastly, an example about fault diagnosis of a steam generator in the nuclear power plant demonstrates the effect of the reasoning algorithm of MFCD, and the result is coincident with the fact. The research shows that the reasoning algorithm of MFCD is so effective to solve the problem of MFCD for fault analysis and reasoning, its reasoning process is rigorous, and the result coincides with the reality.
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