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首页> 外文期刊>Intelligent automation and soft computing >Fault Diagnoses of Hydraulic Turbine Using the Dimension Root Similarity Measure of Single-valued Neutrosophic Sets
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Fault Diagnoses of Hydraulic Turbine Using the Dimension Root Similarity Measure of Single-valued Neutrosophic Sets

机译:基于单值中智集的维根相似度量的水轮机故障诊断

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摘要

This paper proposes a dimension root distance and its similarity measure of single-valued neutrosophic sets (SVNSs), and then develops the fault diagnosis method of hydraulic turbine by using the dimension root similarity measure of SVNSs. By the similarity measures between the fault diagnosis patterns and a testing sample with single-valued neutrosophic information and the relation indices, we can determine the main fault type and the ranking order of various vibration faults for predicting some possible fault trend. Then, the comparison of the fault diagnoses of hydraulic turbine based of the proposed dimension root similarity measure and the existing cotangent similarity measure of SVNSs is provided to demonstrate the effectiveness and rationality of the proposed fault diagnosis method. The fault diagnosis results of hydraulic turbine show that the proposed fault diagnosis method not only gives the main fault types of hydraulic turbine, but also provides useful information for multi-fault analyses and future possible fault trends. The developed fault diagnosis method is effective and reasonable in the fault diagnosis of hydraulic turbine under single-valued neutrosophic environment.
机译:提出了单值中智集(SVNS)的维根距离及其相似性度量,然后利用SVNS的维根相似性度量开发了水轮机故障诊断方法。通过故障诊断模式与具有单值中智信息和相关指标的测试样本之间的相似性度量,我们可以确定主要故障类型和各种振动故障的排序顺序,以预测一些可能的故障趋势。然后,基于提出的维数根相似度测度和现有的SVNSs切向相似度测度对水轮机故障诊断进行了比较,证明了该方法的有效性和合理性。水轮机的故障诊断结果表明,所提出的故障诊断方法不仅给出了水轮机的主要故障类型,而且为多故障分析和未来可能的故障趋势提供了有用的信息。提出的故障诊断方法在单值中性环境下的水轮机故障诊断中是有效,合理的。

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