基于时频的频带熵方法在滚动轴承故障识别中的应用

PDF(1227 KB)

振动与冲击 ›› 2012, Vol. 31 ›› Issue (18) : 29-33.

论文

基于时频的频带熵方法在滚动轴承故障识别中的应用

王小玲 , 陈进 , 从飞云

作者信息 +

Application of spectrum band entropy method in rolling bearings fault diagnosisbased on time-frequency analysis

WANG Xiao-ling, CHEN Jin, CONG Fei-yun

Author information +

文章历史 +

摘要

在信号处理中，现有的常规指标如峭度、峰值、裕度以及谱峭度等对信号因偶然因素引起的数据奇异通常十分敏感，在轴承的状态监测中容易引起误判断。针对这一问题，提出了基于时频的频带熵方法。对信号进行时频变换，再沿时间轴计算各个频率上的幅值谱熵，得到信号的频带熵，以此为特征进行轴承故障的识别。频带熵表征频率成分随时间变化的的复杂性。正常与故障状态的轴承信号频率成分变化的复杂性不同，其频带熵也就不同，因此可将频带熵用于轴承故障的识别。同时偶然因素引起的数据奇异对频率成分变化的复杂性影响很小，频带熵可自动消解这些因素的影响，从而减少对轴承状态的误判断。将频带熵方法用于实际滚动轴承故障的识别，并与峭度、峰值、谱峭度指标对比，证明频带熵能够有效排除数据奇异的干扰，准确判别轴承状态，具有实用性。

Abstract

In signal processing, existing conventional indicators such as kurtosis, peak, margin, spectral kurtosis and other factors are usually very sensitive to accidental singularity on the signal data, which results in false judgments in bearing condition monitoring. To solve this problem, a spectrum band entropy (SBE) methods based on time-frequency is proposed. First, have a time-frequency transform to the signal, and then calculate the spectrum entropy of each frequency along the time axis, which is the SBE of the signal, and it can be used as a feature for bearing fault identification. SBE characterizes the complexity of frequency components change with time. The complexity is different for bearings’ normal state and fault state, and the performance of SBE is different too, so it can be used for bearings fault identification. At the same time, the data singularity caused by causal factors has little effect to the complexity of the frequency components change, SBE can automatically shield these effects, thereby reducing the false judgments. It’s proved to be effective for SBE applied in actual bearing failure identification. Compared with kurtosis, peak, spectral kurtosis and other indicators, SBE can effectively exclude interference from data, and identify the bearing state accurately.

导出引用

王小玲; 陈进; 从飞云. 基于时频的频带熵方法在滚动轴承故障识别中的应用[J]. 振动与冲击, 2012, 31(18): 29-33

WANG Xiao-ling;CHEN Jin;CONG Fei-yun. Application of spectrum band entropy method in rolling bearings fault diagnosisbased on time-frequency analysis[J]. Journal of Vibration and Shock, 2012, 31(18): 29-33