An improved EMD method for fault diagnosis of rolling bearing

Yongbo Li; Minqiang Xu; Wenhu Huang; Ming J. Zuo; Libin Liu

doi:10.1109/PHM.2016.7819842

An improved EMD method for fault diagnosis of rolling bearing

Yongbo Li, Minqiang Xu, Wenhu Huang, Ming J. Zuo, Libin Liu

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

9 Scopus citations

Abstract

Empirical mode decomposition (EMD) is powerful in analyzing the vibration signals of bearings. However, the accuracy of its decomposition result is heavily dependent on the choice of envelope interpolation algorithms. In this paper, we propose a bandwidth method to select the envelope in EMD called bandwidth based EMD (BEMD). Since there is an optimization process in envelope selection, the scale mixing problem caused by envelope interpolation can be significantly weakened. The proposed BEMD method is demonstrated to be effective in rolling bearing fault diagnosis by comparing with existing improved EMD.

Original language	English
Title of host publication	Proceedings of 2016 Prognostics and System Health Management Conference, PHM-Chengdu 2016
Editors	Qiang Miao, Zhaojun Li, Ming J. Zuo, Liudong Xing, Zhigang Tian
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781509027781
DOIs	https://doi.org/10.1109/PHM.2016.7819842
State	Published - 16 Jan 2017
Externally published	Yes
Event	7th IEEE Prognostics and System Health Management Conference, PHM-Chengdu 2016 - Chengdu, Sichuan, China Duration: 19 Oct 2016 → 21 Oct 2016

Publication series

Name	Proceedings of 2016 Prognostics and System Health Management Conference, PHM-Chengdu 2016

Conference

Conference	7th IEEE Prognostics and System Health Management Conference, PHM-Chengdu 2016
Country/Territory	China
City	Chengdu, Sichuan
Period	19/10/16 → 21/10/16

Keywords

Bandwidth based empirical mode decomposition (BEMD)
Fault signature extraction
Rolling bearing

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10.1109/PHM.2016.7819842

Cite this

Li, Y., Xu, M., Huang, W., Zuo, M. J., & Liu, L. (2017). An improved EMD method for fault diagnosis of rolling bearing. In Q. Miao, Z. Li, M. J. Zuo, L. Xing, & Z. Tian (Eds.), Proceedings of 2016 Prognostics and System Health Management Conference, PHM-Chengdu 2016 Article 7819842 (Proceedings of 2016 Prognostics and System Health Management Conference, PHM-Chengdu 2016). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/PHM.2016.7819842

Li, Yongbo ; Xu, Minqiang ; Huang, Wenhu et al. / An improved EMD method for fault diagnosis of rolling bearing. Proceedings of 2016 Prognostics and System Health Management Conference, PHM-Chengdu 2016. editor / Qiang Miao ; Zhaojun Li ; Ming J. Zuo ; Liudong Xing ; Zhigang Tian. Institute of Electrical and Electronics Engineers Inc., 2017. (Proceedings of 2016 Prognostics and System Health Management Conference, PHM-Chengdu 2016).

@inproceedings{9a000d71487d47c6858641e736a58904,

title = "An improved EMD method for fault diagnosis of rolling bearing",

abstract = "Empirical mode decomposition (EMD) is powerful in analyzing the vibration signals of bearings. However, the accuracy of its decomposition result is heavily dependent on the choice of envelope interpolation algorithms. In this paper, we propose a bandwidth method to select the envelope in EMD called bandwidth based EMD (BEMD). Since there is an optimization process in envelope selection, the scale mixing problem caused by envelope interpolation can be significantly weakened. The proposed BEMD method is demonstrated to be effective in rolling bearing fault diagnosis by comparing with existing improved EMD.",

keywords = "Bandwidth based empirical mode decomposition (BEMD), Fault signature extraction, Rolling bearing",

author = "Yongbo Li and Minqiang Xu and Wenhu Huang and Zuo, {Ming J.} and Libin Liu",

note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 7th IEEE Prognostics and System Health Management Conference, PHM-Chengdu 2016 ; Conference date: 19-10-2016 Through 21-10-2016",

year = "2017",

month = jan,

day = "16",

doi = "10.1109/PHM.2016.7819842",

language = "英语",

series = "Proceedings of 2016 Prognostics and System Health Management Conference, PHM-Chengdu 2016",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

editor = "Qiang Miao and Zhaojun Li and Zuo, {Ming J.} and Liudong Xing and Zhigang Tian",

booktitle = "Proceedings of 2016 Prognostics and System Health Management Conference, PHM-Chengdu 2016",

}

Li, Y, Xu, M, Huang, W, Zuo, MJ & Liu, L 2017, An improved EMD method for fault diagnosis of rolling bearing. in Q Miao, Z Li, MJ Zuo, L Xing & Z Tian (eds), Proceedings of 2016 Prognostics and System Health Management Conference, PHM-Chengdu 2016., 7819842, Proceedings of 2016 Prognostics and System Health Management Conference, PHM-Chengdu 2016, Institute of Electrical and Electronics Engineers Inc., 7th IEEE Prognostics and System Health Management Conference, PHM-Chengdu 2016, Chengdu, Sichuan, China, 19/10/16. https://doi.org/10.1109/PHM.2016.7819842

An improved EMD method for fault diagnosis of rolling bearing. / Li, Yongbo; Xu, Minqiang; Huang, Wenhu et al.
Proceedings of 2016 Prognostics and System Health Management Conference, PHM-Chengdu 2016. ed. / Qiang Miao; Zhaojun Li; Ming J. Zuo; Liudong Xing; Zhigang Tian. Institute of Electrical and Electronics Engineers Inc., 2017. 7819842 (Proceedings of 2016 Prognostics and System Health Management Conference, PHM-Chengdu 2016).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - An improved EMD method for fault diagnosis of rolling bearing

AU - Li, Yongbo

AU - Xu, Minqiang

AU - Huang, Wenhu

AU - Zuo, Ming J.

AU - Liu, Libin

PY - 2017/1/16

Y1 - 2017/1/16

N2 - Empirical mode decomposition (EMD) is powerful in analyzing the vibration signals of bearings. However, the accuracy of its decomposition result is heavily dependent on the choice of envelope interpolation algorithms. In this paper, we propose a bandwidth method to select the envelope in EMD called bandwidth based EMD (BEMD). Since there is an optimization process in envelope selection, the scale mixing problem caused by envelope interpolation can be significantly weakened. The proposed BEMD method is demonstrated to be effective in rolling bearing fault diagnosis by comparing with existing improved EMD.

AB - Empirical mode decomposition (EMD) is powerful in analyzing the vibration signals of bearings. However, the accuracy of its decomposition result is heavily dependent on the choice of envelope interpolation algorithms. In this paper, we propose a bandwidth method to select the envelope in EMD called bandwidth based EMD (BEMD). Since there is an optimization process in envelope selection, the scale mixing problem caused by envelope interpolation can be significantly weakened. The proposed BEMD method is demonstrated to be effective in rolling bearing fault diagnosis by comparing with existing improved EMD.

KW - Bandwidth based empirical mode decomposition (BEMD)

KW - Fault signature extraction

KW - Rolling bearing

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U2 - 10.1109/PHM.2016.7819842

DO - 10.1109/PHM.2016.7819842

M3 - 会议稿件

AN - SCOPUS:85015657757

T3 - Proceedings of 2016 Prognostics and System Health Management Conference, PHM-Chengdu 2016

BT - Proceedings of 2016 Prognostics and System Health Management Conference, PHM-Chengdu 2016

A2 - Miao, Qiang

A2 - Li, Zhaojun

A2 - Zuo, Ming J.

A2 - Xing, Liudong

A2 - Tian, Zhigang

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 7th IEEE Prognostics and System Health Management Conference, PHM-Chengdu 2016

Y2 - 19 October 2016 through 21 October 2016

ER -

Li Y, Xu M, Huang W, Zuo MJ, Liu L. An improved EMD method for fault diagnosis of rolling bearing. In Miao Q, Li Z, Zuo MJ, Xing L, Tian Z, editors, Proceedings of 2016 Prognostics and System Health Management Conference, PHM-Chengdu 2016. Institute of Electrical and Electronics Engineers Inc. 2017. 7819842. (Proceedings of 2016 Prognostics and System Health Management Conference, PHM-Chengdu 2016). doi: 10.1109/PHM.2016.7819842

An improved EMD method for fault diagnosis of rolling bearing

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