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首页> 外文期刊>IEEE Transactions on Industry Applications >Fault-Signature Modeling and Detection of Inner-Race Bearing Faults
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Fault-Signature Modeling and Detection of Inner-Race Bearing Faults

机译:内轴承故障的故障特征建模与检测

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摘要

This paper develops a fault-signature model and a fault-detection scheme for using machine vibration to detect inner-race defects. To motivate this research, it is explained and illustrated with experimental results why fault signatures from nonouter-race defects (e.g., inner-race defects) can be less salient than those from outer-race defects. Then, a signal model is presented for the production and propagation of an inner-race fault signature; this model is then used to design an inner-race fault-detection scheme. This scheme examines machine-vibration spectra for peaks with phase-coupled sidebands occurring at a spacing predicted by the model. The proficiency of this fault-detection scheme at detecting inner-race bearing faults is then experimentally verified with results from 12 bearings representing varying degrees of fault severity.
机译:本文提出了一种利用机器振动检测内种族缺陷的故障特征模型和故障检测方案。为了激发这项研究,我们用实验结果来解释和说明为什么非外层缺陷(例如内层缺陷)的故障特征不如外层缺陷的特征显着。然后,提出了一个信号模型,用于内部种族故障特征的产生和传播。然后,使用该模型来设计内部种族故障检测方案。该方案检查机器振动频谱中出现的相耦合边带的峰值,该峰值出现在模型预测的间隔内。然后,通过12个代表不同程度的故障严重性的轴承的结果,通过实验验证了该故障检测方案在检测内圈轴承故障方面的熟练程度。

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