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A Neuro-fuzzy Technique For Fault Diagnosis And Its Application to Rotating Machinery

机译：神经模糊故障诊断技术及其在旋转机械中的应用

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摘要

Malfunctions in machinery are often sources of reduced productivity and increased maintenance costs in various industrial applications. For this reason, machine condition monitoring is being pursued to recognise incipient faults. In this paper, the fault diagnostic problem is tackled within a neuro-fuzzy approach to pattern classification. Besides the primary purpose of a high rate of correct classification, the proposed neuro-fuzzy approach also aims at obtaining an easily interpretable classification model. The efficiency of the approach is verified with respect to a literature problem and then applied to a case of motor bearing fault classification.
机译：在各种工业应用中，机械故障通常是生产率降低和维护成本增加的根源。因此，正在对机器状态进行监视以识别早期故障。在本文中，故障诊断问题是通过模式分类的神经模糊方法解决的。除了高正确分类率的主要目的外，所提出的神经模糊方法还旨在获得易于解释的分类模型。针对文献问题验证了该方法的效率，然后将其应用于电机轴承故障分类的情况。

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