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Diagnosis of Rolling Elements Bearing Based on Inverse Autoregressive Filter

机译:基于逆自回归滤波器的滚动轴承故障诊断

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摘要

Diagnosis of rolling elements bearing plays an important role on the running and maintenance of mechanical equipments.To enhance the feature of fault and to further diagnose the status of bearings with a small fault size so as to realize the early recognition,the method of inverse filter based on Autoregressive model is presented in this paper,and the corresponding criterion of order selection is also discussed.Analysis of simulation signals and real data show that this method could enhance feature of impulse signal.Meanwhile,it is also found that for small size fault,the root mean square feature is more effective than kurtosis value,which is considered very useful for early diagnosis of rolling elements bearings.
机译:滚动轴承的诊断在机械设备的运行和维护中起着重要的作用。为提高故障的特征并进一步诊断故障尺寸较小的轴承的状态,以实现早期识别,采用了逆滤波的方法。本文提出了一种基于自回归模型的模型,并讨论了相应的阶次选择准则。对仿真信号和实际数据的分析表明,该方法可以增强脉冲信号的特性。 ,均方根特征比峰度值更有效,这被认为对滚动轴承的早期诊断非常有用。

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