基于自相关分析与MCKD的滚动轴承早期故障诊断

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振动与冲击 ›› 2019, Vol. 38 ›› Issue (24) : 183-188.

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祝小彦，王永杰

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A method of incipient fault diagnosis of bearings based on autocorrelation analysis and MCKD

ZHU Xiaoyan,WANG Yongjie

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摘要

滚动轴承早期故障信号通常呈现出非平稳性、弱调制性、故障特征成分不突出以及背景噪声强烈等特点，有效提取轴承故障特征比较困难，因此难以准确判断轴承的故障位置。针对这一问题，提出了基于自相关分析与最大相关峭度解卷积（MCKD）算法的滚动轴承故障诊断方法：①利用有偏估计自相关分析方法对轴承信号作初步分析，抑制信号中噪声成分；利用MCKD算法对所得信号作进一步分析，突出信号中的原始冲击成分并进一步去噪，使得信号的信噪比进一步提高；③对信号进行包络谱分析，通过包络谱中的主导频率成分与滚动轴承各元件的故障特征频率对比从而判断轴承的故障位置。仿真数据和实测数据分析结果证明，所提方法能够有效提取故障信号中的特征信息，具有一定的有效性。

Abstract

Rolling bearing early faults often present a non-stationary signal, weak regulation.The fault feature component is not outstanding and there is strong background noise, which makes effective extraction of bearing fault features very difficult.To solve this problem, a fault diagnosis method of rolling bearings based on autocorrelation analysis and MCKD was proposed in this paper.First of all, the use of the biased estimate autocorrelation analysis method of the bearing signal makes a preliminary analysis, realizes the inhibition effect of noise in the signal component, then MCKD solution of the convolution algorithm of the signals was used for further analysis, highlighting the original impact signal components and further de-noising.The signal-to-noise ratio was further improved.Finally, signal envelope spectrum analysis was used to determine the bearing fault location.The simulations and the analysis results of the measured data show that the proposed method can effectively extract the characteristic information of the fault signal and has certain validity.

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祝小彦，王永杰. 基于自相关分析与MCKD的滚动轴承早期故障诊断[J]. 振动与冲击, 2019, 38(24): 183-188

ZHU Xiaoyan,WANG Yongjie. A method of incipient fault diagnosis of bearings based on autocorrelation analysis and MCKD[J]. Journal of Vibration and Shock, 2019, 38(24): 183-188

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