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Fault diagnosis method combining multi-relation indexes with D-S evidence theory

机译:与D-S证据理论相结合多关系指标的故障诊断方法

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The fault diagnosis method based on grey relation analysis needs choosing reference pattern vectors which have a strongly ability of classify and identifying fault, otherwise the veracity and reliability of fault diagnosis can be greatly reduced. On basis of traditional grey relation analysis, multi-samples were adopted as reference signals and the relation indexes between multi-sample reference signals and the signal to be diagnosed are calculated by grey relation analysis method and normalized as the mass or basic probability assignment function which are fused to realize fault diagnosis in term of D-S evidence theory. The method provided in this paper is applied to the fault diagnosis of some reducer case operating state. The simulation result is shown that the reliability of fault diagnosis can be improved by fusion and the uncertainty of fault diagnosis depending on single reference pattern vector can be eliminated too.
机译:基于灰色关系分析的故障诊断方法需要选择具有强大的分类和识别故障的参考模式向量,否则可以大大降低故障诊断的准确性和可靠性。在传统的灰色关系分析的基础上,采用多样样本作为参考信号,并且通过灰色关系分析方法计算多项样品参考信号与要诊断的信号之间的关系指标,并标准化为质量或基本概率分配函数融合在DS证据理论中实现故障诊断。本文提供的方法应用于某些减速器案例运行状态的故障诊断。仿真结果表明,通过融合可以提高故障诊断的可靠性,并且根据单个参考图案向量的故障诊断的不确定性也可以消除。

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