EMD soft-thresholding denoising algorithm for rolling element bearing rotational frequency estimation

被引：3
|
作者：
Cheng W.-D. [1 ]
Zhao D.-Z. [1 ]
机构：
[1] School of Mechanical Electronic and Control Engineering, Beijng Jiaotong University, Beijing
来源：
| 1600年 / Zhejiang University卷 / 50期
关键词：
Empirical mode decomposition (EMD); Instantaneous rotational frequency (IRF) estimation; Rolling element bearing; Signal preprocessing; Soft-thresholding denoising;
D O I：
10.3785/j.issn.1008-973X.2016.03.005
中图分类号：
学科分类号：
摘要：
A method based on the empirical mode decomposition (EMD) and wavelet shrinkage was proposed due to the shortcomings of the EMD cross-correlation coefficient and kurtosis criterion denoising and wavelet shrinkage. The method consists of four main steps: (i) IMFs were obtained by decomposing raw signal, (ii) The cross-correlation coefficient between IMFs and the raw signal, and the kurtosis values of the IMFs were calculated, (iii) IMFs with the noise were selected and the false IMFs were removed, (vi) the noise of the selected IMFs was removed by the soft-thresholding denoising method, and then the signal with the rest of the IMFs was reconstructed. The proposed method was tested based on both the simulated and experimental bearing vibration signals. Results show that, compared with EMD cross-correlation coefficient and kurtosis criterion denoising, the method of EMD soft-thresholding denoising can ensure the integrity of the signal, highlight fault features and reduce the error of the instantaneous rotational frequency (IRF). © 2016, Zhejiang University Press. All right reserved.
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页码：428 / 435
页数：7
相关论文
共 25 条
  • [1] Ming Z., Jing L., Wang X.F., Et al., A tacho-less order tracking technique for large speed variations, Mechanical Systems and Signal Processing, 40, 1, pp. 76-90, (2013)
  • [2] Bonnardot F., Badaoui E.M., Randall R.B., Et al., Use of the acceleration signal of a gearbox in order to perform angular resampling (with limited speed fluctuation), Mechanical Systems and Signal Processing, 19, 4, pp. 766-785, (2005)
  • [3] Urbanek J., Barszcz T., Antoni J., A two-step procedure for estimation of instantaneous rotational speed with large fluctuations, Mechanical System and Signal Processing, 38, pp. 96-102, (2013)
  • [4] Combet F., Zimroz R., A new method for the estimation of the instantaneous speed relative fluctuation in a vibration signal based on the short time scale transform, Mechanical System and Signal Processing, 23, pp. 1382-1397, (2009)
  • [5] Zhao D.Z., Li J.Y., Cheng W.D., Feature extraction of faulty rolling element bearing under variable rotational speed and gear interferences conditions, Shock and Vibration, 2015, pp. 1-9, (2015)
  • [6] Boashash B., Interpreting and estimating the instantaneous frequency of a signal-Part 1: fundamentals, Proceedings of the IEEE, 80, 4, pp. 520-538, (1992)
  • [7] Boashash B., Interpreting and estimating the instantaneous frequency of a signal-Part 2: algorithms and applications, Proceedings of the IEEE, 80, 4, pp. 540-568, (1992)
  • [8] Guo Y., Qin S.-R., Tang B.-P., Et al., Order tracking of rotating machinery based on instantaneous frequency estimation, Chinese Journal of Mechanical Engineering, 39, 3, pp. 32-36, (2003)
  • [9] Zhao X.-P., Zhao X.-L., Hou R.-T., Et al., A new method for instantaneous frequency estimation of run-up or run-down vibration signal for rotating machinery, Chinese Journal of Mechanical Engineering, 47, 7, pp. 103-108, (2011)
  • [10] Wang T.Y., Liang M., Li J.Y., Et al., Rolling element bearing fault diagnosis via fault characteristic order (FCO) analysis, Mechanical System and Signal Processing, 45, 1, pp. 139-153, (2014)
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