基于连续峭度优化的滚动轴承故障特征提取小波变换方法

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振动与冲击 ›› 2015, Vol. 34 ›› Issue (14) : 27-32.

论文

冯毅，曹劲然，陆宝春，张登峰

作者信息 +

A fault feature extraction method for rolling bearing based on wavelet transform optimized by continuous kurtosis

FENG Yi，CAO Jin-ran，LU Bao-chun，ZHANG Deng-feng

Author information +

文章历史 +

摘要

为更有效提取滚动轴承早期故障中微弱冲击特征成分，提出基于连续峭度优化的小波变换故障特征提取方法。据连续峭度与小波能量相关程度，对原信号特征分量的小波系数及能量成分进行不同程度优化，强化故障信号中具有冲击特征的能量成分、削弱其它能量成分。通过优化的小波系数重构原信号特征分量，计算特征分量包络谱以提取冲击特征频率及相关倍频，实现对故障特征提取。通过仿真信号、实际轴承数据应用分析表明，该算法能强化冲击特征能量成分，能更有效提取早期故障中冲击特征。

Abstract

In order to extract the weak impulse component of bearing fault at early stage effectively, an extraction method for bearing fault feature was presented, which was based on wavelet transform optimized by continuous kurtosis. According to the correlation degree between continuous kurtosis and wavelet energy, wavelet coefficients and energy components of the original signal feature component were optimized to varying degrees, and the energy component of impulse feature was strengthened, while the other energy components were weakened. The original signal feature component was reconstructed by optimized wavelet coefficients, and the feature component envelope spectrum was calculated to extract impulse feature frequency and its related multiplier, which achieved the extraction of failure feature. The analysis of simulation signals and the application results of bearing signals show that the algorithm can strengthen the energy component of impulse feature, and extract the impulse feature of incipient fault more effectively than other methods.

导出引用

冯毅，曹劲然，陆宝春，张登峰. 基于连续峭度优化的滚动轴承故障特征提取小波变换方法[J]. 振动与冲击, 2015, 34(14): 27-32

FENG Yi，CAO Jin-ran，LU Bao-chun，ZHANG Deng-feng. A fault feature extraction method for rolling bearing based on wavelet transform optimized by continuous kurtosis[J]. Journal of Vibration and Shock, 2015, 34(14): 27-32

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