48. MED and WPT based technique for bearings fault detection

Zhang Dan1, Sui Wentao2

1School of Electrical and Electronic Engineering, Shandong University of Technology, Zibo 255049, China

2School of Mechanical Engineering, Shandong University of Technology, Zibo 255049, China

2Corresponding author

E-mail: 1zhangdan_sdut@163.com, 2suiwt@163.com

(Received 20 January 2014; received in revised form 18 March 2014; accepted 22 March 2014)

Abstract. A new technique is proposed in this work for fault detection in rolling element bearings, which is based on minimum entropy deconvolution (MED), wavelet packet decomposition (WPT) and envelop analysis. Firstly, the collected vibration signal is preprocessed to highlight defect‑related impulses, and a new indicator named envelope spectra sparsity (ESS) is proposed to automatically select the filter length of MED. Then the preprocessed signal is decomposed into WPT nodes, and the most sensitive node containing fault-related information are selected from all the nodes to improve the accuracy of the fault detection. Sparsity of wavelet packet nodes signal (SWPN) is proposed in this step as a measure indicator. Lastly the power spectrum is used to highlight the bearing fault characteristic frequencies. The effectiveness of the proposed AMED‑WPT technique in feature extraction and analysis is verified by a series of experimental tests corresponding to different bearing conditions.

Keywords: minimum entropy deconvolution, wavelet packet decomposition, envelope analysis, bearing fault.

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Cite this article

Dan Zhang, Wentao Sui MED and WPT based technique for bearings fault detection. Journal of Measurements in Engineering, Vol. 2, Issue 2, 2014, p. 103‑110.

 

Journal of Measurements in Engineering. June 2014, Volume 2, Issue 2
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