基于相关峭度共振解调的滚动轴承复合故障特征分离方法

胡爱军,赵军,孙尚飞,黄申申

振动与冲击 ›› 2019, Vol. 38 ›› Issue (8) : 110-116.

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振动与冲击 ›› 2019, Vol. 38 ›› Issue (8) : 110-116.
论文

基于相关峭度共振解调的滚动轴承复合故障特征分离方法

  • 胡爱军,赵军,孙尚飞,黄申申
作者信息 +

A compound fault feature separation method of rolling bearing based on correlation kurtosis resonance demodulation

  • HU Aijun,ZHAO Jun,SUN Shangfei,HUANG Shenshen
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文章历史 +

摘要

提出了一种基于相关峭度的共振解调方法,并应用于滚动轴承复合故障特征的分离。首先沿频率轴平移一给定滤波窗,计算每个滤波信号的相关峭度;然后通过设定不同的故障移位周期,形成多条故障的相关峭度曲线;最后根据筛选出的目标相关峭度曲线的最大值,确定多个共振频带对原信号进行共振解调。解决了由于某一频带的峭度值过大,利用谱峭度可能无法识别出不同故障各自激起的共振频带的问题。通过不同能量的多共振频带轴承复合故障仿真验证了共振频带选择的准确性,不同载荷下的轴承内、外圈复合故障实测信号分析表明,该方法可以有效实现轴承复合故障特征的分离。

Abstract

A resonant demodulation method based on correlated kurtosis was proposed and applied to the separation of rolling bearing compound fault features.Firstly, a right shifting filter window was defined on the frequency axis, the correlation kurtosis of each filtered signal was calculated; Secondly, the correlated kurtosis curves of multiple faults were formed by setting different fault shift periods.Finally, according to the maximum value in the target correlated kurtosis curve of the selected, several resonance bands were determined to demodulate the original signal.It solves the problem that the resonance frequency band caused by different faults may not be identified by using spectral kurtosis because the kurtosis value of a certain frequency band is too large.The accuracy of resonance band selection was verified by simulation of multiple resonance band bearing compound faults with different energy, the measured signal analysis of compound fault of inner and outer rings of bearings under different loads shows that this method can effectively realize the separation of bearing compound fault features.

关键词

滚动轴承 / 复合故障 / 相关峭度 / 共振解调 / 特征分离

Key words

rolling bearing / compound fault / correlation kurtosis / resonance demodulation / feature separation

引用本文

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胡爱军,赵军,孙尚飞,黄申申. 基于相关峭度共振解调的滚动轴承复合故障特征分离方法[J]. 振动与冲击, 2019, 38(8): 110-116
HU Aijun,ZHAO Jun,SUN Shangfei,HUANG Shenshen. A compound fault feature separation method of rolling bearing based on correlation kurtosis resonance demodulation[J]. Journal of Vibration and Shock, 2019, 38(8): 110-116

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