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The intelligent fault diagnosis frameworks based on fuzzy integral

机译:基于模糊积分的智能故障诊断框架

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Fuzzy integral is an information aggregation and combination process in a multi-criteria environment using fuzzy measures. This paper presents a new data fusion method using fuzzy integral for fault diagnosis. The method consists of two frameworks. The first framework was employed to identify the relations between features and a specified fault. The second framework was implemented to integrate different diagnosis algorithms to improve the accuracy rates of them. The choquet fuzzy integral was utilized for two frameworks. The proposed approach was experimentally implemented on a 0.37 kW induction motor. Broken rotor bar and stator faults were evaluated to validate the models. The results showed that the proposed method performs very well for broken rotor bar and stator faults.
机译:模糊积分是在多准则环境中使用模糊测度的信息聚合和组合过程。本文提出了一种新的基于模糊积分的数据融合方法,用于故障诊断。该方法由两个框架组成。采用第一个框架来识别特征与指定故障之间的关系。实施第二个框架以集成不同的诊断算法,以提高它们的准确率。球拍模糊积分用于两个框架。所提出的方法是在0.37 kW感应电动机上通过实验实现的。对损坏的转子导条和定子故障进行了评估,以验证模型。结果表明,该方法在转子断条和定子故障中表现良好。

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