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An interval-valued hesitant fuzzy multigranulation rough set over two universes model for steam turbine fault diagnosis

机译:两个宇宙模型的区间值犹豫模糊多粒度粗糙集用于汽轮机故障诊断

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In the field of mechanical engineering, steam turbine fault diagnosis is a difficult task for mechanical engineers who are confronted with challenges in dealing with copious amounts of uncertain information. Different mechanical engineers may have their own opinions about the system fault knowledge base that differs slightly from other mechanical engineers. Thus, to solve the problems presented by uncertain data analysis and group decision-making in steam turbine fault diagnosis, we propose a new rough set model that combines interval-valued hesitant fuzzy sets with multigranulation rough sets over two universes, called an interval-valued hesitant fuzzy multigranulation rough set over two universes. In the multigranulation framework, both basic definitions and some important properties of the proposed model are presented. Then, we develop a general approach to steam turbine fault diagnosis by using the proposed model. Lastly, an illustrative example is provided to verify the established approach and demonstrate its validity and applicability.
机译:在机械工程领域,对于处理大量不确定信息的机械工程师而言,汽轮机故障诊断是一项艰巨的任务。不同的机械工程师对系统故障知识库的看法可能与其他机械工程师略有不同。因此,为了解决汽轮机故障诊断中不确定数据分析和群体决策提出的问题,我们提出了一种新的粗糙集模型,该模型将区间值犹豫模糊集与两个领域的多粒度粗糙集相结合,称为区间值在两个宇宙上设置犹豫的模糊多粒度粗糙集。在多粒度框架中,提出了模型的基本定义和一些重要属性。然后,我们使用提出的模型开发了一种用于汽轮机故障诊断的通用方法。最后,提供了一个示例性例子来验证所建立的方法并证明其有效性和适用性。

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