Various faults inevitably occur in mechanical systems and may result in unexpected failures. Hence, fault detection is critical to reduce unscheduled downtime and costly breakdowns. Empirical mode decomposition (EMD) is an adaptive time-frequency domain signal processing method, potentially suitable for nonstationary and/or nonlinear processes. However, the EMD method suffers from several problems such as mode mixing, defined as intrinsic mode functions (IMFs) with incorrect scales. In this paper, an ensemble noise-reconstructed EMD method is proposed to ameliorate the mode mixing problem and denoise IMFs for enhancing fault signatures. The proposed method defines the IMF components as an ensemble mean of EMD trials, where each trial is obtained by sifting signals that have been reconstructed using the estimated noise present in the measured signal. Unlike traditional denoising methods, the noise inherent in the input data is reconstructed and used to reduce the background noise. Furthermore, the reconstructed noise helps to project different scales of the signal onto their corresponding IMFs, instrumental in alleviating the mode mixing problem. Two critical issues concerned in the method, i.e., the noise estimation strategy and the number of EMD trials required for denoising are discussed. Furthermore, a comprehensive noise-assisted EMD method is proposed, which includes the proposed method and ensemble EMD (EEMD). Numerical simulations and experimental case studies on accelerometer data collected from an industrial shaving process are used to demonstrate and validate the proposed method. Results show that the proposed method can both detect impending faults and isolate multiple faults. Hence, the proposed method can act as a promising tool for mechanical fault detection.
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April 2013
Research-Article
Ensemble Noise-Reconstructed Empirical Mode Decomposition for Mechanical Fault Detection
Jing Yuan,
Jing Yuan
State Key Laboratory for Manufacturing and Systems Engineering,
School of Mechanical Engineering,
Xi'an 710049, PR
Department of Mechanical Engineering,
Ann Arbor, MI, 48109
e-mail: yuanjng@gmail.com
School of Mechanical Engineering,
Xi'an Jiaotong University
,Xi'an 710049, PR
China
;Department of Mechanical Engineering,
University of Michigan
,Ann Arbor, MI, 48109
e-mail: yuanjng@gmail.com
Search for other works by this author on:
Zhengjia He,
Zhengjia He
State Key Laboratory for Manufacturing and Systems Engineering,
School of Mechanical Engineering,
Xi'an 710049, PR
e-mail: hzj@mail.xjtu.edu.cn
School of Mechanical Engineering,
Xi'an Jiaotong University
,Xi'an 710049, PR
China
e-mail: hzj@mail.xjtu.edu.cn
Search for other works by this author on:
Jun Ni,
Jun Ni
Department of Mechanical Engineering,
Ann Arbor, MI, 48109
e-mail: junni@umich.edu
University of Michigan
,Ann Arbor, MI, 48109
e-mail: junni@umich.edu
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Adam John Brzezinski,
Adam John Brzezinski
Department of Aerospace Engineering,
Ann Arbor,
48109 e-mail: bigtalladam@gmail.com
University of Michigan
,Ann Arbor,
MI
,48109 e-mail: bigtalladam@gmail.com
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Yanyang Zi
Yanyang Zi
State Key Laboratory for Manufacturing and Systems Engineering,
School of Mechanical Engineering,
Xi'an 710049, PR
e-mail: ziyy@mail.xjtu.edu.cn
School of Mechanical Engineering,
Xi'an Jiaotong University
,Xi'an 710049, PR
China
e-mail: ziyy@mail.xjtu.edu.cn
Search for other works by this author on:
Jing Yuan
State Key Laboratory for Manufacturing and Systems Engineering,
School of Mechanical Engineering,
Xi'an 710049, PR
Department of Mechanical Engineering,
Ann Arbor, MI, 48109
e-mail: yuanjng@gmail.com
School of Mechanical Engineering,
Xi'an Jiaotong University
,Xi'an 710049, PR
China
;Department of Mechanical Engineering,
University of Michigan
,Ann Arbor, MI, 48109
e-mail: yuanjng@gmail.com
Zhengjia He
State Key Laboratory for Manufacturing and Systems Engineering,
School of Mechanical Engineering,
Xi'an 710049, PR
e-mail: hzj@mail.xjtu.edu.cn
School of Mechanical Engineering,
Xi'an Jiaotong University
,Xi'an 710049, PR
China
e-mail: hzj@mail.xjtu.edu.cn
Jun Ni
Department of Mechanical Engineering,
Ann Arbor, MI, 48109
e-mail: junni@umich.edu
University of Michigan
,Ann Arbor, MI, 48109
e-mail: junni@umich.edu
Adam John Brzezinski
Department of Aerospace Engineering,
Ann Arbor,
48109 e-mail: bigtalladam@gmail.com
University of Michigan
,Ann Arbor,
MI
,48109 e-mail: bigtalladam@gmail.com
Yanyang Zi
State Key Laboratory for Manufacturing and Systems Engineering,
School of Mechanical Engineering,
Xi'an 710049, PR
e-mail: ziyy@mail.xjtu.edu.cn
School of Mechanical Engineering,
Xi'an Jiaotong University
,Xi'an 710049, PR
China
e-mail: ziyy@mail.xjtu.edu.cn
Contributed by the Design Engineering Division of ASME for publication in the JOURNAL OF VIBRATION AND ACOUSTICS. Manuscript received October 19, 2010; final manuscript received August 12, 2012; published online March 18, 2013. Assoc. Editor: Brian Feeny.
J. Vib. Acoust. Apr 2013, 135(2): 021011 (16 pages)
Published Online: March 18, 2013
Article history
Received:
October 19, 2010
Revision Received:
August 12, 2012
Citation
Yuan, J., He, Z., Ni, J., Brzezinski, A. J., and Zi, Y. (March 18, 2013). "Ensemble Noise-Reconstructed Empirical Mode Decomposition for Mechanical Fault Detection." ASME. J. Vib. Acoust. April 2013; 135(2): 021011. https://doi.org/10.1115/1.4023138
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