An Intelligent Approach for Bearing Fault Diagnosis Based on Bayesian Networks and Alpha-Stable Distribution

Gang Yu; Lazhuan Zhang

doi:10.1109/CICN.2015.24

An Intelligent Approach for Bearing Fault Diagnosis Based on Bayesian Networks and Alpha-Stable Distribution

Gang Yu
, Lazhuan Zhang

Harbin Institute of Technology Shenzhen

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

4 Scopus citations

Abstract

In the field of fault diagnosis, neural networks have been widely applied in distinguishing the type of fault. However, neural networks require training with large number of sample data, and as the input of neural networks, fault pattern vectors does not guarantee that can completely represent faults. Bayesian networks (BN) is a powerful method widely used to solve the problem with uncertainty and incomplete information. Alpha-stable distribution model is effective to describe the statistical characteristics of machine fault signal with impulsive behaviors. Therefore, the combination of the alpha-stable distribution parameters and Bayesian networks for a new intelligent diagnosis method is proposed. The results prove that the proposed method is effective for bearing fault diagnosis.

Original language	English
Title of host publication	Proceedings - 2015 International Conference on Computational Intelligence and Communication Networks, CICN 2015
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	76-78
Number of pages	3
ISBN (Electronic)	9781509000760
DOIs	https://doi.org/10.1109/CICN.2015.24
State	Published - 16 Aug 2016
Externally published	Yes
Event	7th International Conference on Computational Intelligence and Communication Networks, CICN 2015 - Jabalpur, India Duration: 12 Dec 2015 → 14 Dec 2015

Publication series

Name	Proceedings - 2015 International Conference on Computational Intelligence and Communication Networks, CICN 2015

Conference

Conference	7th International Conference on Computational Intelligence and Communication Networks, CICN 2015
Country/Territory	India
City	Jabalpur
Period	12/12/15 → 14/12/15

Keywords

Bayesian networks
alpha-stable distribution
bearing fault diagnosis

Access to Document

10.1109/CICN.2015.24

Cite this

Yu, G., & Zhang, L. (2016). An Intelligent Approach for Bearing Fault Diagnosis Based on Bayesian Networks and Alpha-Stable Distribution. In Proceedings - 2015 International Conference on Computational Intelligence and Communication Networks, CICN 2015 (pp. 76-78). Article 7546059 (Proceedings - 2015 International Conference on Computational Intelligence and Communication Networks, CICN 2015). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CICN.2015.24

Yu, Gang ; Zhang, Lazhuan. / An Intelligent Approach for Bearing Fault Diagnosis Based on Bayesian Networks and Alpha-Stable Distribution. Proceedings - 2015 International Conference on Computational Intelligence and Communication Networks, CICN 2015. Institute of Electrical and Electronics Engineers Inc., 2016. pp. 76-78 (Proceedings - 2015 International Conference on Computational Intelligence and Communication Networks, CICN 2015).

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title = "An Intelligent Approach for Bearing Fault Diagnosis Based on Bayesian Networks and Alpha-Stable Distribution",

abstract = "In the field of fault diagnosis, neural networks have been widely applied in distinguishing the type of fault. However, neural networks require training with large number of sample data, and as the input of neural networks, fault pattern vectors does not guarantee that can completely represent faults. Bayesian networks (BN) is a powerful method widely used to solve the problem with uncertainty and incomplete information. Alpha-stable distribution model is effective to describe the statistical characteristics of machine fault signal with impulsive behaviors. Therefore, the combination of the alpha-stable distribution parameters and Bayesian networks for a new intelligent diagnosis method is proposed. The results prove that the proposed method is effective for bearing fault diagnosis.",

keywords = "Bayesian networks, alpha-stable distribution, bearing fault diagnosis",

author = "Gang Yu and Lazhuan Zhang",

note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; 7th International Conference on Computational Intelligence and Communication Networks, CICN 2015 ; Conference date: 12-12-2015 Through 14-12-2015",

year = "2016",

month = aug,

day = "16",

doi = "10.1109/CICN.2015.24",

language = "英语",

series = "Proceedings - 2015 International Conference on Computational Intelligence and Communication Networks, CICN 2015",

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

pages = "76--78",

booktitle = "Proceedings - 2015 International Conference on Computational Intelligence and Communication Networks, CICN 2015",

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Yu, G & Zhang, L 2016, An Intelligent Approach for Bearing Fault Diagnosis Based on Bayesian Networks and Alpha-Stable Distribution. in Proceedings - 2015 International Conference on Computational Intelligence and Communication Networks, CICN 2015., 7546059, Proceedings - 2015 International Conference on Computational Intelligence and Communication Networks, CICN 2015, Institute of Electrical and Electronics Engineers Inc., pp. 76-78, 7th International Conference on Computational Intelligence and Communication Networks, CICN 2015, Jabalpur, India, 12/12/15. https://doi.org/10.1109/CICN.2015.24

An Intelligent Approach for Bearing Fault Diagnosis Based on Bayesian Networks and Alpha-Stable Distribution. / Yu, Gang; Zhang, Lazhuan.
Proceedings - 2015 International Conference on Computational Intelligence and Communication Networks, CICN 2015. Institute of Electrical and Electronics Engineers Inc., 2016. p. 76-78 7546059 (Proceedings - 2015 International Conference on Computational Intelligence and Communication Networks, CICN 2015).

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

TY - GEN

T1 - An Intelligent Approach for Bearing Fault Diagnosis Based on Bayesian Networks and Alpha-Stable Distribution

AU - Yu, Gang

AU - Zhang, Lazhuan

PY - 2016/8/16

Y1 - 2016/8/16

N2 - In the field of fault diagnosis, neural networks have been widely applied in distinguishing the type of fault. However, neural networks require training with large number of sample data, and as the input of neural networks, fault pattern vectors does not guarantee that can completely represent faults. Bayesian networks (BN) is a powerful method widely used to solve the problem with uncertainty and incomplete information. Alpha-stable distribution model is effective to describe the statistical characteristics of machine fault signal with impulsive behaviors. Therefore, the combination of the alpha-stable distribution parameters and Bayesian networks for a new intelligent diagnosis method is proposed. The results prove that the proposed method is effective for bearing fault diagnosis.

AB - In the field of fault diagnosis, neural networks have been widely applied in distinguishing the type of fault. However, neural networks require training with large number of sample data, and as the input of neural networks, fault pattern vectors does not guarantee that can completely represent faults. Bayesian networks (BN) is a powerful method widely used to solve the problem with uncertainty and incomplete information. Alpha-stable distribution model is effective to describe the statistical characteristics of machine fault signal with impulsive behaviors. Therefore, the combination of the alpha-stable distribution parameters and Bayesian networks for a new intelligent diagnosis method is proposed. The results prove that the proposed method is effective for bearing fault diagnosis.

KW - Bayesian networks

KW - alpha-stable distribution

KW - bearing fault diagnosis

UR - https://www.scopus.com/pages/publications/84985898146

U2 - 10.1109/CICN.2015.24

DO - 10.1109/CICN.2015.24

M3 - 会议稿件

AN - SCOPUS:84985898146

T3 - Proceedings - 2015 International Conference on Computational Intelligence and Communication Networks, CICN 2015

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BT - Proceedings - 2015 International Conference on Computational Intelligence and Communication Networks, CICN 2015

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 7th International Conference on Computational Intelligence and Communication Networks, CICN 2015

Y2 - 12 December 2015 through 14 December 2015

ER -

Yu G, Zhang L. An Intelligent Approach for Bearing Fault Diagnosis Based on Bayesian Networks and Alpha-Stable Distribution. In Proceedings - 2015 International Conference on Computational Intelligence and Communication Networks, CICN 2015. Institute of Electrical and Electronics Engineers Inc. 2016. p. 76-78. 7546059. (Proceedings - 2015 International Conference on Computational Intelligence and Communication Networks, CICN 2015). doi: 10.1109/CICN.2015.24

An Intelligent Approach for Bearing Fault Diagnosis Based on Bayesian Networks and Alpha-Stable Distribution

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