毕达哥拉斯模糊集在故障诊断中的应用

Hoang Nguyen
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引用次数: 0

摘要

摘要本文对基于普通模糊集、Atanassov的直觉模糊集及其扩展的方法进行了全面的回顾和批判分析,揭示了它们的局限性和缺陷。然后,引入了一种新的基于广义分数函数的相似性度量,该度量包含了信息的显著性(重要性),使其更直观地进行比较。将该方法应用于毕达哥拉斯模糊环境下的汽轮发电机组故障诊断。将旋转机械的10种故障类型建立为9个不同振动频率范围内的故障模式,并用毕达哥拉斯模糊数表示。通过与现有方法的数值算例比较,证明了该方法在处理不确定和模糊信息方面的优越性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Application of the Pythagorean Fuzzy Sets in the Fault Diagnosis
Abstract In this paper, a comprehensive review and critical analyses of methods based on the ordinary fuzzy set, Atanassov’s intuitionistic fuzzy set, and its extensions have been conducted to show their limitations and defects. Then, a novel similarity measure based on the generalized score function has been introduced that incorporates the significance (importance) of information, making it more intuitive to compare them. The proposed method is employed for the fault diagnosis of steam turbine generator unit under Pythagorean fuzzy environment. Ten fault types of rotating machines are established as failure patterns in nine different vibration frequency ranges, expressed in terms of Pythagorean fuzzy numbers. The superiority of the proposed method in dealing with uncertain and vague information is shown by comparing it with some existing measures in numerical examples.
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