An adaptive demodulation approach for bearing fault detection based on adaptive wavelet.pdf

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An adaptive demodulation approach for bearing fault detection based on adaptive wavelet.pdf

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An adaptive demodulation approach for bearing fault detection based on adaptive wavelet

This content has been downloaded from IOPscience. Please scroll down to see the full text. Download details: IP Address: 42 This content was downloaded on 20/12/2015 at 12:53 Please note that terms and conditions apply. An adaptive demodulation approach for bearing fault detection based on adaptive wavelet filtering and spectral subtraction View the table of contents for this issue, or go to the journal homepage for more 2016 Meas. Sci. Technol. 27 025001 (/0957-0233/27/2/025001) Home Search Collections Journals About Contact us My IOPscience 1 ? 2016 IOP Publishing Ltd Printed in the UK Yan?Zhang1, Baoping?Tang1,2, Ziran?Liu2 and Rengxiang?Chen1 1 State Key Laboratory of Mechanical Transmission, Chongqing University, Chongqing 400044, People’s Republic of China 2 School of Mechanical Electrical Engineering, Henan University of Technology, Zhengzhou 450007, People’s Republic of China E-mail: bptang@ Received 29 July 2015, revised 27 October 2015 Accepted for publication 3 November 2015 Published 18 December 2015 Abstract Fault diagnosis of rolling element bearings is important for improving mechanical system reliability and performance. Vibration signals contain a wealth of complex information useful for state monitoring and fault diagnosis. However, any fault-related impulses in the original signal are often severely tainted by various noises and the interfering vibrations caused by other machine elements. Narrow-band amplitude demodulation has been an effective technique to detect bearing faults by identifying bearing fault characteristic frequencies. To achieve this, the key step is to remove the corrupting noise and interference, and to enhance the weak signatures of the bearing fault. In this paper, a new method based on adaptive wavelet filtering and spectral subtraction is proposed for fault diagnosis in bearings. First, to eliminate the frequency associated with interfering vibrations, the vibration signal is bandpass filtered with a Morlet wav