Fractional Envelope Analysis for Rolling Element Bearing Weak Fault Feature Extraction

Jianhong Wang; Liyan Qiao; Yongqiang Ye; YangQuan Chen

doi:10.1109/JAS.2016.7510166

Volume 4 Issue 2

Apr. 2017

IEEE/CAA Journal of Automatica Sinica

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Article Navigation > IEEE/CAA Journal of Automatica Sinica > 2017 > 4(2): 353-360

Jianhong Wang, Liyan Qiao, Yongqiang Ye and YangQuan Chen, "Fractional Envelope Analysis for Rolling Element Bearing Weak Fault Feature Extraction," IEEE/CAA J. Autom. Sinica, vol. 4, no. 2, pp. 353-360, Apr. 2017. doi: 10.1109/JAS.2016.7510166

Citation:

Jianhong Wang, Liyan Qiao, Yongqiang Ye and YangQuan Chen, "Fractional Envelope Analysis for Rolling Element Bearing Weak Fault Feature Extraction," IEEE/CAA J. Autom. Sinica, vol. 4, no. 2, pp. 353-360, Apr. 2017. doi: 10.1109/JAS.2016.7510166

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Fractional Envelope Analysis for Rolling Element Bearing Weak Fault Feature Extraction

doi: 10.1109/JAS.2016.7510166

1.
School of Science, Nantong University, Nantong 226019, China
2.
School of Engineering, University of California, Merced CA 95343, USA
3.
College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China

Funds:

This work was supported by National Natural Science Foundation of China 61074161

This work was supported by National Natural Science Foundation of China 61273103

This work was supported by National Natural Science Foundation of China 61374061

and Nantong Science and Technology Plan Project MS22016051

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Author Bio:
Liyan Qiao received the B. S. degree in radio engineering from Harbin Institute of Technology, China, in 1992, the M. S. degree in communication and electronics system from Harbin Institute of Technology, China, in 1996, and the Ph. D. degree in instrumentation science and technology from Harbin Institute of Technology, China, in 2005. He is at the Automatic Test and Control Faculty of School of Electrical Engineering and Automation, Harbin Institute of Technology, Harbin, China. His research interests include automatic test system, data acquiring technic through internet, flash storage system, and signal analysis.(e-mail: qiaoliyan@163.com)

Yongqiang Ye received the B. S. and M. S. degrees from Zhejiang University, China, in 1994 and 1997, respectively, and the Ph. D. degree from Nanyang Technological University, Singapore, in 2004, all in electrical engineering. He had been a faculty member with the School of Information, Zhejiang University of Finance and Economics, China, for more than four years. He had also been a postdoctoral fellow with the Department of Electrical Engineering at Lakehead University, the Department of Systems and Computer Engineering at Carleton University, and the Department of Mechanical Engineering, Dalhousie University, Canada, respectively. He joined the Department of Automation Engineering at Nanjing University of Aeronautics and Astronautics in 2009 as a professor. He is a Senior Member of IEEE. His research interests include computer vision, pattern recognition, learning and repetitive control, and power electronics control.(e-mail: melvinye@nuaa.edu.cn)

YangQuan Chen received his Ph. D. degree in advanced control and instrumentation from Nanyang Technological University, Singapore, in 1998. Dr. Chen was on the Faculty of Electrical and Computer Engineering at Utah State University before he joined the School of Engineering, University of California, Merced in 2012 where he teaches "Mechatronics" for juniors and "Fractional Order Mechanics" for graduates. His current research interests include mechatronics for sustainability, cognitive process control and hybrid lighting control, multi-UAV based cooperative multi-spectral "personal remote sensing" and applications, applied fractional calculus in controls, signal processing and energy informatics; distributed measurement and distributed control of distributed parameter systems using mobile actuator and sensor networks.(e-mail: yqchen@ieee.org)
Corresponding author: Jianhong Wang received the B. S. degree in mathematics and applied mathematics from Jiangsu Normal University, China, in 2000, the M. S. degree in operations research and control theory from Shanghai Jiao Tong University, China, in 2007, and the Ph. D. degree in control theory and control engineering from Nanjing University of Aeronautics and Astronautics, China, in 2016. He was a visiting scholar with the School of Engineering at the University of California, Merced, USA, in 2015. He is currently an associate professor at the School of Science, Nantong University, China. His current research interests include applied fractional calculus in intelligent control, signal processing, image processing, and big data processing. Corresponding author of this paper.(e-mail: ntuwjh@163.com)
Received Date: 2015-09-11
Accepted Date: 2016-03-15

Abstract

Abstract

The bearing weak fault feature extraction is crucial to mechanical fault diagnosis and machine condition monitoring. Envelope analysis based on Hilbert transform has been widely used in bearing fault feature extraction. A generalization of the Hilbert transform, the fractional Hilbert transform is defined in the frequency domain, it is based upon the modification of spatial filter with a fractional parameter, and it can be used to construct a new kind of fractional analytic signal. By performing spectrum analysis on the fractional envelope signal, the fractional envelope spectrum can be obtained. When weak faults occur in a bearing, some of the characteristic frequencies will clearly appear in the fractional envelope spectrum. These characteristic frequencies can be used for bearing weak fault feature extraction. The effectiveness of the proposed method is verified through simulation signal and experiment data.
- Fractional analytic signal,
- fractional envelope analysis,
- fractional Hilbert transform,
- rolling element bearing,
- weak fault feature extraction

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References(22)

References

[1]	N. Sawalhi, R. B. Randall, and H. Endo, "The enhancement of fault detection and diagnosis in rolling element bearings using minimum entropy deconvolution combined with spectral kurtosis, " Mech. Syst. Signal Process. , vol. 21, no. 6, pp. 2616-2633, Aug. 2007. http://www.sciencedirect.com/science/article/pii/S0888327006002603
[2]	S. Yin, S. X. Ding, X. C. Xie, and H. Luo, "A review on basic data-driven approaches for industrial process monitoring, " IEEE Trans. Ind. Electron. , vol. 61, no. 11, pp. 6418-6428, Nov. 2014. http://ieeexplore.ieee.org/document/6717991/
[3]	B. P. Cai, Y. H. Liu, Q. Fan, Y. W. Zhang, Z. K. Liu, S. L. Yu, and R. J. Ji, "Multi-source information fusion based fault diagnosis of ground-source heat pump using Bayesian network, " Appl. Energy, vol. 114, pp. 1-9, Feb. 2014. http://www.sciencedirect.com/science/article/pii/S0306261913007903
[4]	W. Sun, G. A. Yang, Q. Chen, A. Palazoglu, and K. Feng, "Fault diagnosis of rolling bearing based on wavelet transform and envelope spectrum correlation, " J. Vib. Control, vol. 19, no. 6, pp. 924-941, Apr. 2013. http://www.sciencedirect.com/science/article/pii/S0888327004000354
[5]	R. B. Randall and J. Antoni, "Rolling element bearing diagnostics-a tutorial, " Mech. Syst. Signal Process. , vol. 25, no. 2, pp. 485-520, Feb. 2011. https://en.wikipedia.org/wiki/Rolling-element_bearing
[6]	Y. Ming, J. Chen, and G. M. Dong, "Weak fault feature extraction of rolling bearing based on cyclic Wiener filter and envelope spectrum, " Mech. Syst. Signal Process. , vol. 25, no. 5, pp. 1773-1785, Jul. 2011. http://www.sciencedirect.com/science/article/pii/S0888327010004267
[7]	P. Borghesani, P. Pennacchi, and S. Chatterton, "The relationship between kurtosis-and envelope-based indexes for the diagnostic of rolling element bearings, " Mech. Syst. Signal Process. , vol. 43, no. 1-2, pp. 25-43, Feb. 2014. http://www.sciencedirect.com/science/article/pii/S0888327013005104
[8]	A. B. Ming, W. Zhang, Z. Y. Qin, and F. L. Chu, "Envelope calculation of the multi-component signal and its application to the deterministic component cancellation in bearing fault diagnosis, " Mech. Syst. Signal Process. , vol. 50-51, pp. 70-100, Jan. 2015. http://www.sciencedirect.com/science/article/pii/S088832701400209X
[9]	R. H. Jiang, S. L. Liu, Y. F. Tang, and Y. H. Liu, "A novel method of fault diagnosis for rolling element bearings based on the accumulated envelope spectrum of the wavelet packet, " J. Vib. Control, vol. 21, no. 8, pp. 1580-1593, Jun. 2015. https://www.hindawi.com/journals/mpe/2016/5432648/
[10]	M. Feldman, "Hilbert transform in vibration analysis, " Mech. Syst. Signal Process. , vol. 25, no. 3, pp. 735-802, Apr. 2011. http://www.sciencedirect.com/science/article/pii/S0888327010002542
[11]	M. Feldman, Hilbert Transform Applications in Mechanical Vibration. Chichester, UK: John Wiley and Sons, 2011.
[12]	A. W. Lohmann, D. Mendlovic, and Z. Zalevsky, "Fractional Hilbert transform, " Opt. Lett. , vol. 21, no. 4, pp. 281-283, Feb. 1996. http://www.mina.ubc.ca/biblio/fractional-hilbert-tran
[13]	S. C. Pei and M. H. Yeh, "Discrete fractional Hilbert transform, " IEEE Trans. Circ. Syst. Ⅱ: Analog Digit. Signal Process. , vol. 47, no. 11, pp. 1307-1311, Nov. 2000. http://www.academia.edu/4303068/Discrete_fractional_Hilbert_transform
[14]	C. C. Tseng and S. C. Pei, "Design and application of discrete-time fractional Hilbert transformer, " IEEE Trans. Circ. Syst. Ⅱ: Analog Digit. Signal Process. , vol. 47, no. 12, pp. 1529-1533, Dec. 2000. http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=899647
[15]	F. W. King, Hilbert Transforms. Cambridge, UK: Cambridge University Press, 2009.
[16]	C. A. Monje, Y. Q. Chen, B. M. Vinagre, D. Y. Xue, and V. Feliu, Fractional-order Systems and Controls: Fundamentals and Applications. London, UK: Springer, 2010.
[17]	J. Antoni and R. B. Randall, "The spectral Kurtosis: Application to the vibratory surveillance and diagnostics of rotating machines, " Mech. Syst. Signal Process. , vol. 20, no. 2, pp. 308-331, Feb. 2006. http://www.sciencedirect.com/science/article/pii/S0888327004001529
[18]	L. T. DeCarlo, "On the meaning and use of kurtosis, " Psychol. Methods, vol. 2, no. 3, pp. 292-307, Sep. 1997. https://themeaningofthename.com/kur/
[19]	L. Saidi, J. B. Ali, and F. Fnaiech, "The use of spectral kurtosis as a trend parameter for bearing faults diagnosis, " in Proc. 15th Int. Conf. Sciences and Techniques of Automatic Control and Computer Engineering, Hammamet, Tunisia, 2014, pp. 394-399.
[20]	L. Saidi, J. B. Ali, and F. Fnaiech, "Bi-spectrum based-EMD applied to the non-stationary vibration signals for bearing faults diagnosis, " ISA Trans. , vol. 53, no. 5, pp. 1650-1660, Sep. 2014. https://www.ncbi.nlm.nih.gov/pubmed/24975564
[21]	K. A. Loparo, Bearings vibration data set. Case Western Reserve University. [Online]. Available: http://csegroups.case.edu/bearingdatacenter/pages/12k-drive-end-bearing-fault-data.
[22]	L. Saidi, J. B. Ali, and F. Fnaiech, "Application of higher order spectral features and support vector machines for bearing faults classification, " ISA Trans. , vol. 54, pp. 193-206, Jan. 2015. http://www.sciencedirect.com/science/article/pii/S0019057814002043

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Fractional Envelope Analysis for Rolling Element Bearing Weak Fault Feature Extraction

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