改进小波阈值函数和ACEWT方法的滚动轴承故障声发射信号特征提取

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摘要针对滚动轴承早期故障声发射信号受复杂传递路径和噪声的干扰，声发射信号信噪比较低，导致轴承故障特征难以提取的问题，提出了改进小波阈值函数-ACEWT的轴承故障特征提取方法。由于声发射信号呈冲击性与快速衰减的特点，构建一种衰减正弦型与指数型的小波阈值函数对低信噪比的声发射信号进行降噪。研究自相关运算与经验小波变换结合的方法(autocorrelation and empirical wavelet transform，ACEWT)，用于滚动轴承故障声发射信号特征提取，解决了在低信噪比下经验小波变换对轴承故障特征提取的不足；引入经验小波能量比-熵指标，选取最优经验小波系数。通过与经验小波变换、改进小波阈值函数-EWT和MCKD-EWT方法进行对比研究，并实验验证。仿真和实验结果表明：所提方法明显优于经验小波变换、改进小波阈值函数-EWT和MCKD-EWT方法，可准确提取轴承故障声发射信号的频率特征。

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	于洋1
	李赟1
	杨平1
	杨学广2
	梁哲铭3

关键词 ：声发射, 滚动轴承, 衰减型阈值函数, 经验小波变换

Abstract：The early fault acoustic emission signal of rolling bearing is affected by complex transmission paths and strong background noise, which makes the fault features difficult to extract. An improved wavelet threshold function -ACEWT (autocorrelation and empirical wavelet transform) method was proposed.Due to the characteristics of impulsiveness and rapid attenuation of acoustic emission signal, an attenuated sinusoidal and exponential wavelet threshold function method was proposed to denoise acoustic emission signal with low signal-to-noise ratio.The method of combining autocorrelation and empirical wavelet transform (ACEWT) was proposed to bearing fault diagnosis. ACEWT method solves the problem that the empirical wavelet transform cannot effectively extract fault features.Introduce the empirical wavelet energy ratio-entropy index to select the optimal empirical wavelet coefficients.The new method can denoise the signal and enhance the periodic elastic impact components feature with low signal-to-noise ratio.The simulated and experimental results show that the proposed method is obviously better than empirical wavelet transform (EWT), improved wavelet threshold function-EWT and Maximum correlated kurtosis deconvolution-empirical wavelet transform (MCKD-EWT).The proposed method can accurately extract the frequency characteristics of fault signal.

Key words： acoustic emission rolling bearing attenuation threshold function empirical wavelet transform

收稿日期: 2022-05-16 出版日期: 2023-09-15

引用本文:

于洋1，李赟1，杨平1，杨学广2，梁哲铭3. 改进小波阈值函数和ACEWT方法的滚动轴承故障声发射信号特征提取[J]. 振动与冲击, 2023, 42(17): 194-202.
YU Yang1, LI Yun1, YANG Ping1, YANG Xueguang2, LIANG Zheming3. Improved wavelet threshold function and ACEWT method for feature extraction of acoustic emission signals from rolling bearing faults. JOURNAL OF VIBRATION AND SHOCK, 2023, 42(17): 194-202.

链接本文:

http://jvs.sjtu.edu.cn/CN/ 或 http://jvs.sjtu.edu.cn/CN/Y2023/V42/I17/194

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