A diagnosis method for diesel engine wear fault based on grey rough set and SOM neural network

Silin Qian; Shenghan Zhou; Wenbing Chang; Yiyong Xiao; Fajie Wei

A diagnosis method for diesel engine wear fault based on grey rough set and SOM neural network

Beihang University

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

Abstract

The paper aims to establish a model to identify wear fault of marine diesel engine based on grey rough set and Self-Organizing Map (SOM) network with oil monitoring data analysis. The empirical data indicates the wear fault takes great proportion in fault types of diesel engine. Through oil monitoring, the change of parameters of lubricating oil and the information of wear particle can be obtained to analyze status of components. Firstly, the paper constructs the two-dimensional fault decision table. Subsequently, the grey relational analysis and rough set theory are used to reduce the fault decision table horizontally and longitudinally. Next, the fault diagnosis model is established by SOM network. Finally, the proposed model is validated by empirical research. The result suggests that the proposed model is feasible in wear fault diagnosis problem. Moreover, compared with the traditional SOM neural network, the model has less error and better diagnosis effect.

Original language	English
Title of host publication	Safety and Reliability - Safe Societies in a Changing World - Proceedings of the 28th International European Safety and Reliability Conference, ESREL 2018
Editors	Coen van Gulijk, Stein Haugen, Anne Barros, Jan Erik Vinnem, Trond Kongsvik
Publisher	CRC Press/Balkema
Pages	995-1002
Number of pages	8
ISBN (Print)	9780815386827
State	Published - 2018
Event	28th International European Safety and Reliability Conference, ESREL 2018 - Trondheim, Norway Duration: 17 Jun 2018 → 21 Jun 2018

Publication series

Name	Safety and Reliability - Safe Societies in a Changing World - Proceedings of the 28th International European Safety and Reliability Conference, ESREL 2018

Conference

Conference	28th International European Safety and Reliability Conference, ESREL 2018
Country/Territory	Norway
City	Trondheim
Period	17/06/18 → 21/06/18

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 14 Life Below Water

Cite this

Qian, S., Zhou, S., Chang, W., Xiao, Y., & Wei, F. (2018). A diagnosis method for diesel engine wear fault based on grey rough set and SOM neural network. In C. van Gulijk, S. Haugen, A. Barros, J. E. Vinnem, & T. Kongsvik (Eds.), Safety and Reliability - Safe Societies in a Changing World - Proceedings of the 28th International European Safety and Reliability Conference, ESREL 2018 (pp. 995-1002). (Safety and Reliability - Safe Societies in a Changing World - Proceedings of the 28th International European Safety and Reliability Conference, ESREL 2018). CRC Press/Balkema.

Qian, Silin ; Zhou, Shenghan ; Chang, Wenbing et al. / A diagnosis method for diesel engine wear fault based on grey rough set and SOM neural network. Safety and Reliability - Safe Societies in a Changing World - Proceedings of the 28th International European Safety and Reliability Conference, ESREL 2018. editor / Coen van Gulijk ; Stein Haugen ; Anne Barros ; Jan Erik Vinnem ; Trond Kongsvik. CRC Press/Balkema, 2018. pp. 995-1002 (Safety and Reliability - Safe Societies in a Changing World - Proceedings of the 28th International European Safety and Reliability Conference, ESREL 2018).

@inproceedings{b8a3890af0ac4b35bac6582d2af678ef,

title = "A diagnosis method for diesel engine wear fault based on grey rough set and SOM neural network",

abstract = "The paper aims to establish a model to identify wear fault of marine diesel engine based on grey rough set and Self-Organizing Map (SOM) network with oil monitoring data analysis. The empirical data indicates the wear fault takes great proportion in fault types of diesel engine. Through oil monitoring, the change of parameters of lubricating oil and the information of wear particle can be obtained to analyze status of components. Firstly, the paper constructs the two-dimensional fault decision table. Subsequently, the grey relational analysis and rough set theory are used to reduce the fault decision table horizontally and longitudinally. Next, the fault diagnosis model is established by SOM network. Finally, the proposed model is validated by empirical research. The result suggests that the proposed model is feasible in wear fault diagnosis problem. Moreover, compared with the traditional SOM neural network, the model has less error and better diagnosis effect.",

author = "Silin Qian and Shenghan Zhou and Wenbing Chang and Yiyong Xiao and Fajie Wei",

note = "Publisher Copyright: {\textcopyright} 2018 Taylor \& Francis Group, London.; 28th International European Safety and Reliability Conference, ESREL 2018 ; Conference date: 17-06-2018 Through 21-06-2018",

year = "2018",

language = "英语",

isbn = "9780815386827",

series = "Safety and Reliability - Safe Societies in a Changing World - Proceedings of the 28th International European Safety and Reliability Conference, ESREL 2018",

publisher = "CRC Press/Balkema",

pages = "995--1002",

editor = "\{van Gulijk\}, Coen and Stein Haugen and Anne Barros and Vinnem, \{Jan Erik\} and Trond Kongsvik",

booktitle = "Safety and Reliability - Safe Societies in a Changing World - Proceedings of the 28th International European Safety and Reliability Conference, ESREL 2018",

}

Qian, S, Zhou, S , Chang, W , Xiao, Y & Wei, F 2018, A diagnosis method for diesel engine wear fault based on grey rough set and SOM neural network. in C van Gulijk, S Haugen, A Barros, JE Vinnem & T Kongsvik (eds), Safety and Reliability - Safe Societies in a Changing World - Proceedings of the 28th International European Safety and Reliability Conference, ESREL 2018. Safety and Reliability - Safe Societies in a Changing World - Proceedings of the 28th International European Safety and Reliability Conference, ESREL 2018, CRC Press/Balkema, pp. 995-1002, 28th International European Safety and Reliability Conference, ESREL 2018, Trondheim, Norway, 17/06/18.

A diagnosis method for diesel engine wear fault based on grey rough set and SOM neural network. / Qian, Silin; Zhou, Shenghan ; Chang, Wenbing et al.
Safety and Reliability - Safe Societies in a Changing World - Proceedings of the 28th International European Safety and Reliability Conference, ESREL 2018. ed. / Coen van Gulijk; Stein Haugen; Anne Barros; Jan Erik Vinnem; Trond Kongsvik. CRC Press/Balkema, 2018. p. 995-1002 (Safety and Reliability - Safe Societies in a Changing World - Proceedings of the 28th International European Safety and Reliability Conference, ESREL 2018).

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

TY - GEN

T1 - A diagnosis method for diesel engine wear fault based on grey rough set and SOM neural network

AU - Qian, Silin

AU - Zhou, Shenghan

AU - Chang, Wenbing

AU - Xiao, Yiyong

AU - Wei, Fajie

PY - 2018

Y1 - 2018

N2 - The paper aims to establish a model to identify wear fault of marine diesel engine based on grey rough set and Self-Organizing Map (SOM) network with oil monitoring data analysis. The empirical data indicates the wear fault takes great proportion in fault types of diesel engine. Through oil monitoring, the change of parameters of lubricating oil and the information of wear particle can be obtained to analyze status of components. Firstly, the paper constructs the two-dimensional fault decision table. Subsequently, the grey relational analysis and rough set theory are used to reduce the fault decision table horizontally and longitudinally. Next, the fault diagnosis model is established by SOM network. Finally, the proposed model is validated by empirical research. The result suggests that the proposed model is feasible in wear fault diagnosis problem. Moreover, compared with the traditional SOM neural network, the model has less error and better diagnosis effect.

AB - The paper aims to establish a model to identify wear fault of marine diesel engine based on grey rough set and Self-Organizing Map (SOM) network with oil monitoring data analysis. The empirical data indicates the wear fault takes great proportion in fault types of diesel engine. Through oil monitoring, the change of parameters of lubricating oil and the information of wear particle can be obtained to analyze status of components. Firstly, the paper constructs the two-dimensional fault decision table. Subsequently, the grey relational analysis and rough set theory are used to reduce the fault decision table horizontally and longitudinally. Next, the fault diagnosis model is established by SOM network. Finally, the proposed model is validated by empirical research. The result suggests that the proposed model is feasible in wear fault diagnosis problem. Moreover, compared with the traditional SOM neural network, the model has less error and better diagnosis effect.

UR - https://www.scopus.com/pages/publications/85058118313

M3 - 会议稿件

AN - SCOPUS:85058118313

SN - 9780815386827

T3 - Safety and Reliability - Safe Societies in a Changing World - Proceedings of the 28th International European Safety and Reliability Conference, ESREL 2018

SP - 995

EP - 1002

BT - Safety and Reliability - Safe Societies in a Changing World - Proceedings of the 28th International European Safety and Reliability Conference, ESREL 2018

A2 - van Gulijk, Coen

A2 - Haugen, Stein

A2 - Barros, Anne

A2 - Vinnem, Jan Erik

A2 - Kongsvik, Trond

PB - CRC Press/Balkema

T2 - 28th International European Safety and Reliability Conference, ESREL 2018

Y2 - 17 June 2018 through 21 June 2018

ER -

Qian S, Zhou S , Chang W , Xiao Y , Wei F. A diagnosis method for diesel engine wear fault based on grey rough set and SOM neural network. In van Gulijk C, Haugen S, Barros A, Vinnem JE, Kongsvik T, editors, Safety and Reliability - Safe Societies in a Changing World - Proceedings of the 28th International European Safety and Reliability Conference, ESREL 2018. CRC Press/Balkema. 2018. p. 995-1002. (Safety and Reliability - Safe Societies in a Changing World - Proceedings of the 28th International European Safety and Reliability Conference, ESREL 2018).

A diagnosis method for diesel engine wear fault based on grey rough set and SOM neural network

Abstract

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UN SDGs

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