Cooling fan bearing diagnosis based on AR& MED

Chaoqin Liu, Xue Zhou, Shuai Yang, Wei Liang, Q. Miao
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引用次数: 5

Abstract

To monitor the initial failure of cooling fan's rolling bearing, this paper reviews the theory of autoregressive (AR) model and the minimum entropy deconvolution (MED) filtering technique. The AR method can remove the deterministic components of the original signal, and the MED filter could reduce the effect of the transmission path. These two filtering techniques were combined in this paper to pre-process the rolling bearing's vibration signal, and then the envelope spectrum of the residual signal was analyzed. The method leads to efficient filtering result.
基于ar和MED的冷却风扇轴承诊断
为了监测冷却风扇滚动轴承的初始故障,本文综述了自回归(AR)模型理论和最小熵反卷积(MED)滤波技术。AR方法可以去除原始信号中的不确定性成分,MED滤波器可以减小传输路径的影响。本文将这两种滤波技术结合起来对滚动轴承振动信号进行预处理,然后对残差信号的包络谱进行分析。该方法具有较好的滤波效果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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