The vibration signal decomposition is a critical step in the assessment of machine health condition. Though ensemble empirical mode decomposition (EEMD) method outperforms fast Fourier transform (FFT), wavelet transform, and empirical mode decomposition (EMD) on nonstationary signal decomposition, there exists a mode mixing problem if the two critical parameters (i.e., the amplitude of added white noise and the number of ensemble trials) are not selected appropriately. A novel EEMD method with optimized two parameters is proposed to solve the mode mixing problem in vibration signal decomposition in this paper. In the proposed optimal EEMD, the initial values of the two critical parameters are selected based on an adaptive algorithm. Then, a multimode search algorithm is explored to optimize the critical two parameters by its good performance in global and local search. The performances of the proposed method are demonstrated by means of a simulated signal, two bearing vibration signals, and a vibration signal in a milling process. The results show that compared with the traditional EEMD method and other improved EEMD method, the proposed optimal EEMD method automatically obtains the appropriate parameters of EEMD and achieves higher decomposition accuracy and faster computational efficiency.
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June 2017
Research-Article
An Optimal Ensemble Empirical Mode Decomposition Method for Vibration Signal Decomposition
Shi-Chang Du,
Shi-Chang Du
State Key Lab of Mechanical
System and Vibration;
System and Vibration;
Department of Industrial
Engineering and Management,
School of Mechanical Engineering,
Shanghai Jiaotong University,
Shanghai 200240, China
e-mail: lovbin@sjtu.edu.cn
Engineering and Management,
School of Mechanical Engineering,
Shanghai Jiaotong University,
Shanghai 200240, China
e-mail: lovbin@sjtu.edu.cn
Search for other works by this author on:
Tao Liu,
Tao Liu
Department of Industrial
Engineering and Management,
School of Mechanical Engineering,
Shanghai Jiaotong University,
Shanghai 200240, China
e-mail: l_yz2007@163.com
Engineering and Management,
School of Mechanical Engineering,
Shanghai Jiaotong University,
Shanghai 200240, China
e-mail: l_yz2007@163.com
Search for other works by this author on:
De-Lin Huang,
De-Lin Huang
Department of Industrial
Engineering and Management,
School of Mechanical Engineering,
Shanghai Jiaotong University,
Shanghai 200240, China
e-mail: cjwanan@sjtu.edu.cn
Engineering and Management,
School of Mechanical Engineering,
Shanghai Jiaotong University,
Shanghai 200240, China
e-mail: cjwanan@sjtu.edu.cn
Search for other works by this author on:
Gui-Long Li
Gui-Long Li
Department of Industrial
Engineering and Management,
School of Mechanical Engineering,
Shanghai Jiaotong University,
Shanghai 200240, China
e-mail: lgllg68629315@qq.com
Engineering and Management,
School of Mechanical Engineering,
Shanghai Jiaotong University,
Shanghai 200240, China
e-mail: lgllg68629315@qq.com
Search for other works by this author on:
Shi-Chang Du
State Key Lab of Mechanical
System and Vibration;
System and Vibration;
Department of Industrial
Engineering and Management,
School of Mechanical Engineering,
Shanghai Jiaotong University,
Shanghai 200240, China
e-mail: lovbin@sjtu.edu.cn
Engineering and Management,
School of Mechanical Engineering,
Shanghai Jiaotong University,
Shanghai 200240, China
e-mail: lovbin@sjtu.edu.cn
Tao Liu
Department of Industrial
Engineering and Management,
School of Mechanical Engineering,
Shanghai Jiaotong University,
Shanghai 200240, China
e-mail: l_yz2007@163.com
Engineering and Management,
School of Mechanical Engineering,
Shanghai Jiaotong University,
Shanghai 200240, China
e-mail: l_yz2007@163.com
De-Lin Huang
Department of Industrial
Engineering and Management,
School of Mechanical Engineering,
Shanghai Jiaotong University,
Shanghai 200240, China
e-mail: cjwanan@sjtu.edu.cn
Engineering and Management,
School of Mechanical Engineering,
Shanghai Jiaotong University,
Shanghai 200240, China
e-mail: cjwanan@sjtu.edu.cn
Gui-Long Li
Department of Industrial
Engineering and Management,
School of Mechanical Engineering,
Shanghai Jiaotong University,
Shanghai 200240, China
e-mail: lgllg68629315@qq.com
Engineering and Management,
School of Mechanical Engineering,
Shanghai Jiaotong University,
Shanghai 200240, China
e-mail: lgllg68629315@qq.com
1Corresponding author.
Contributed by the Technical Committee on Vibration and Sound of ASME for publication in the JOURNAL OF VIBRATION AND ACOUSTICS. Manuscript received August 24, 2016; final manuscript received November 29, 2016; published online March 16, 2017. Assoc. Editor: Mohammed Daqaq.
J. Vib. Acoust. Jun 2017, 139(3): 031003 (18 pages)
Published Online: March 16, 2017
Article history
Received:
August 24, 2016
Revised:
November 29, 2016
Citation
Du, S., Liu, T., Huang, D., and Li, G. (March 16, 2017). "An Optimal Ensemble Empirical Mode Decomposition Method for Vibration Signal Decomposition." ASME. J. Vib. Acoust. June 2017; 139(3): 031003. https://doi.org/10.1115/1.4035480
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