BP Neural Network Based Fault Diagnosis in Vehicle Braking Control System

Mengjie Huang; Jiyan Wang; Rui Yang

doi:10.1109/IMCEC.2018.8469266

BP Neural Network Based Fault Diagnosis in Vehicle Braking Control System

Mengjie Huang^*, Jiyan Wang, Rui Yang

^*Corresponding author for this work

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

2 Citations (Scopus)

Abstract

W232 the popularity of the high-speed railway in China, its operation safety issues has been attracting more and more attention nowadays. How to improve the high-speed railway reliability has become an emerging research focus. This paper investigated the fault diagnosis in vehicle braking control system, which is a core subsystem of EMU (electric multiple unit). To diagnosis the sensor fault in braking control system, back propagation (BP) neural network based method with two different learning approaches were utilized and compared. Test results based on raw data collected from EMU experimental platform showed that both approaches can accurately diagnose the faults, while the moment based learning approach provided a faster outcome compared with conventional gradient descent approach.

Original language	English
Title of host publication	Proceedings of 2018 2nd IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2018
Editors	Bing Xu
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	794-798
Number of pages	5
ISBN (Electronic)	9781538618035
DOIs	https://doi.org/10.1109/IMCEC.2018.8469266
Publication status	Published - 20 Sept 2018
Externally published	Yes
Event	2nd IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2018 - Xi'an, China Duration: 25 May 2018 → 27 May 2018

Publication series

Name	Proceedings of 2018 2nd IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2018

Conference

Conference	2nd IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2018
Country/Territory	China
City	Xi'an
Period	25/05/18 → 27/05/18

Keywords

braking system
fault diagnosis
neural network

Access to Document

10.1109/IMCEC.2018.8469266

Cite this

Huang, M., Wang, J., & Yang, R. (2018). BP Neural Network Based Fault Diagnosis in Vehicle Braking Control System. In B. Xu (Ed.), Proceedings of 2018 2nd IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2018 (pp. 794-798). Article 8469266 (Proceedings of 2018 2nd IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2018). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IMCEC.2018.8469266

Huang, Mengjie ; Wang, Jiyan ; Yang, Rui. / BP Neural Network Based Fault Diagnosis in Vehicle Braking Control System. Proceedings of 2018 2nd IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2018. editor / Bing Xu. Institute of Electrical and Electronics Engineers Inc., 2018. pp. 794-798 (Proceedings of 2018 2nd IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2018).

@inproceedings{1241f4d9d95a442d85bd9965e81750c3,

title = "BP Neural Network Based Fault Diagnosis in Vehicle Braking Control System",

abstract = "W232 the popularity of the high-speed railway in China, its operation safety issues has been attracting more and more attention nowadays. How to improve the high-speed railway reliability has become an emerging research focus. This paper investigated the fault diagnosis in vehicle braking control system, which is a core subsystem of EMU (electric multiple unit). To diagnosis the sensor fault in braking control system, back propagation (BP) neural network based method with two different learning approaches were utilized and compared. Test results based on raw data collected from EMU experimental platform showed that both approaches can accurately diagnose the faults, while the moment based learning approach provided a faster outcome compared with conventional gradient descent approach.",

keywords = "braking system, fault diagnosis, neural network",

author = "Mengjie Huang and Jiyan Wang and Rui Yang",

note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 2nd IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2018 ; Conference date: 25-05-2018 Through 27-05-2018",

year = "2018",

month = sep,

day = "20",

doi = "10.1109/IMCEC.2018.8469266",

language = "English",

series = "Proceedings of 2018 2nd IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2018",

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

pages = "794--798",

editor = "Bing Xu",

booktitle = "Proceedings of 2018 2nd IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2018",

}

Huang, M, Wang, J & Yang, R 2018, BP Neural Network Based Fault Diagnosis in Vehicle Braking Control System. in B Xu (ed.), Proceedings of 2018 2nd IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2018., 8469266, Proceedings of 2018 2nd IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2018, Institute of Electrical and Electronics Engineers Inc., pp. 794-798, 2nd IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2018, Xi'an, China, 25/05/18. https://doi.org/10.1109/IMCEC.2018.8469266

BP Neural Network Based Fault Diagnosis in Vehicle Braking Control System. / Huang, Mengjie; Wang, Jiyan; Yang, Rui.
Proceedings of 2018 2nd IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2018. ed. / Bing Xu. Institute of Electrical and Electronics Engineers Inc., 2018. p. 794-798 8469266 (Proceedings of 2018 2nd IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2018).

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

TY - GEN

T1 - BP Neural Network Based Fault Diagnosis in Vehicle Braking Control System

AU - Huang, Mengjie

AU - Wang, Jiyan

AU - Yang, Rui

PY - 2018/9/20

Y1 - 2018/9/20

N2 - W232 the popularity of the high-speed railway in China, its operation safety issues has been attracting more and more attention nowadays. How to improve the high-speed railway reliability has become an emerging research focus. This paper investigated the fault diagnosis in vehicle braking control system, which is a core subsystem of EMU (electric multiple unit). To diagnosis the sensor fault in braking control system, back propagation (BP) neural network based method with two different learning approaches were utilized and compared. Test results based on raw data collected from EMU experimental platform showed that both approaches can accurately diagnose the faults, while the moment based learning approach provided a faster outcome compared with conventional gradient descent approach.

AB - W232 the popularity of the high-speed railway in China, its operation safety issues has been attracting more and more attention nowadays. How to improve the high-speed railway reliability has become an emerging research focus. This paper investigated the fault diagnosis in vehicle braking control system, which is a core subsystem of EMU (electric multiple unit). To diagnosis the sensor fault in braking control system, back propagation (BP) neural network based method with two different learning approaches were utilized and compared. Test results based on raw data collected from EMU experimental platform showed that both approaches can accurately diagnose the faults, while the moment based learning approach provided a faster outcome compared with conventional gradient descent approach.

KW - braking system

KW - fault diagnosis

KW - neural network

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U2 - 10.1109/IMCEC.2018.8469266

DO - 10.1109/IMCEC.2018.8469266

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T3 - Proceedings of 2018 2nd IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2018

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BT - Proceedings of 2018 2nd IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2018

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PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2nd IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2018

Y2 - 25 May 2018 through 27 May 2018

ER -

Huang M, Wang J, Yang R. BP Neural Network Based Fault Diagnosis in Vehicle Braking Control System. In Xu B, editor, Proceedings of 2018 2nd IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2018. Institute of Electrical and Electronics Engineers Inc. 2018. p. 794-798. 8469266. (Proceedings of 2018 2nd IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2018). doi: 10.1109/IMCEC.2018.8469266

BP Neural Network Based Fault Diagnosis in Vehicle Braking Control System

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