An Investigation of Unsupervised Data-Driven Models for Internal Combustion Engine Condition Monitoring

Xiaoxia Liang; Chao Fu; Xiuquan Sun; Fang Duan; David Mba; Fengshou Gu; Andrew D. Ball

doi:10.1007/978-3-030-99075-6_38

An Investigation of Unsupervised Data-Driven Models for Internal Combustion Engine Condition Monitoring

Xiaoxia Liang
, Chao Fu^*
, Xiuquan Sun
, Fang Duan
, David Mba
, Fengshou Gu
, Andrew D. Ball

^*Corresponding author for this work

London South Bank University
Hebei University of Technology
University of Huddersfield
De Montfort University

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

1 Citation (Scopus)

Original language	English
Title of host publication	Proceedings of IncoME-VI and TEPEN 2021 - Performance Engineering and Maintenance Engineering
Editors	Hao Zhang, Guojin Feng, Hongjun Wang, Fengshou Gu, Jyoti K. Sinha
Publisher	Springer Science and Business Media B.V.
Pages	463-475
Number of pages	13
ISBN (Print)	9783030990749
DOIs	https://doi.org/10.1007/978-3-030-99075-6_38
Publication status	Published (VoR) - 2023
Event	6th International Conference on Maintenance Engineering, IncoME-VI and the Conference of the Efficiency and Performance Engineering Network, TEPEN 2021 - Tianjin, China Duration: 20 Oct 2021 → 23 Oct 2021

Publication series

Name	Mechanisms and Machine Science
Volume	117
ISSN (Print)	2211-0984
ISSN (Electronic)	2211-0992

Conference

Conference	6th International Conference on Maintenance Engineering, IncoME-VI and the Conference of the Efficiency and Performance Engineering Network, TEPEN 2021
Country/Territory	China
City	Tianjin
Period	20/10/21 → 23/10/21

Keywords

Fault detection
IC engine
Lubrication system filter blocking
Misfire
Unsupervised machine learning

Access to Document

10.1007/978-3-030-99075-6_38

Cite this

Liang, X., Fu, C., Sun, X., Duan, F., Mba, D., Gu, F., & Ball, A. D. (2023). An Investigation of Unsupervised Data-Driven Models for Internal Combustion Engine Condition Monitoring. In H. Zhang, G. Feng, H. Wang, F. Gu, & J. K. Sinha (Eds.), Proceedings of IncoME-VI and TEPEN 2021 - Performance Engineering and Maintenance Engineering (pp. 463-475). (Mechanisms and Machine Science; Vol. 117). Springer Science and Business Media B.V.. https://doi.org/10.1007/978-3-030-99075-6_38

Liang, Xiaoxia ; Fu, Chao ; Sun, Xiuquan et al. / An Investigation of Unsupervised Data-Driven Models for Internal Combustion Engine Condition Monitoring. Proceedings of IncoME-VI and TEPEN 2021 - Performance Engineering and Maintenance Engineering. editor / Hao Zhang ; Guojin Feng ; Hongjun Wang ; Fengshou Gu ; Jyoti K. Sinha. Springer Science and Business Media B.V., 2023. pp. 463-475 (Mechanisms and Machine Science).

@inproceedings{79dd5661dbaf4b4e85aee6322b3d7399,

title = "An Investigation of Unsupervised Data-Driven Models for Internal Combustion Engine Condition Monitoring",

keywords = "Fault detection, IC engine, Lubrication system filter blocking, Misfire, Unsupervised machine learning",

author = "Xiaoxia Liang and Chao Fu and Xiuquan Sun and Fang Duan and David Mba and Fengshou Gu and Ball, \{Andrew D.\}",

note = "Publisher Copyright: {\textcopyright} 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.; 6th International Conference on Maintenance Engineering, IncoME-VI and the Conference of the Efficiency and Performance Engineering Network, TEPEN 2021 ; Conference date: 20-10-2021 Through 23-10-2021",

year = "2023",

doi = "10.1007/978-3-030-99075-6\_38",

language = "English",

isbn = "9783030990749",

series = "Mechanisms and Machine Science",

publisher = "Springer Science and Business Media B.V.",

pages = "463--475",

editor = "Hao Zhang and Guojin Feng and Hongjun Wang and Fengshou Gu and Sinha, \{Jyoti K.\}",

booktitle = "Proceedings of IncoME-VI and TEPEN 2021 - Performance Engineering and Maintenance Engineering",

}

Liang, X, Fu, C, Sun, X, Duan, F, Mba, D, Gu, F & Ball, AD 2023, An Investigation of Unsupervised Data-Driven Models for Internal Combustion Engine Condition Monitoring. in H Zhang, G Feng, H Wang, F Gu & JK Sinha (eds), Proceedings of IncoME-VI and TEPEN 2021 - Performance Engineering and Maintenance Engineering. Mechanisms and Machine Science, vol. 117, Springer Science and Business Media B.V., pp. 463-475, 6th International Conference on Maintenance Engineering, IncoME-VI and the Conference of the Efficiency and Performance Engineering Network, TEPEN 2021, Tianjin, China, 20/10/21. https://doi.org/10.1007/978-3-030-99075-6_38

An Investigation of Unsupervised Data-Driven Models for Internal Combustion Engine Condition Monitoring. / Liang, Xiaoxia; Fu, Chao; Sun, Xiuquan et al.
Proceedings of IncoME-VI and TEPEN 2021 - Performance Engineering and Maintenance Engineering. ed. / Hao Zhang; Guojin Feng; Hongjun Wang; Fengshou Gu; Jyoti K. Sinha. Springer Science and Business Media B.V., 2023. p. 463-475 (Mechanisms and Machine Science; Vol. 117).

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

TY - GEN

T1 - An Investigation of Unsupervised Data-Driven Models for Internal Combustion Engine Condition Monitoring

AU - Liang, Xiaoxia

AU - Fu, Chao

AU - Sun, Xiuquan

AU - Duan, Fang

AU - Mba, David

AU - Gu, Fengshou

AU - Ball, Andrew D.

PY - 2023

Y1 - 2023

KW - Fault detection

KW - IC engine

KW - Lubrication system filter blocking

KW - Misfire

KW - Unsupervised machine learning

UR - https://www.scopus.com/pages/publications/85138795038

UR - https://www.scopus.com/pages/publications/85138795038#tab=citedBy

U2 - 10.1007/978-3-030-99075-6_38

DO - 10.1007/978-3-030-99075-6_38

M3 - Conference contribution

AN - SCOPUS:85138795038

SN - 9783030990749

T3 - Mechanisms and Machine Science

SP - 463

EP - 475

BT - Proceedings of IncoME-VI and TEPEN 2021 - Performance Engineering and Maintenance Engineering

A2 - Zhang, Hao

A2 - Feng, Guojin

A2 - Wang, Hongjun

A2 - Gu, Fengshou

A2 - Sinha, Jyoti K.

PB - Springer Science and Business Media B.V.

T2 - 6th International Conference on Maintenance Engineering, IncoME-VI and the Conference of the Efficiency and Performance Engineering Network, TEPEN 2021

Y2 - 20 October 2021 through 23 October 2021

ER -

Liang X, Fu C, Sun X, Duan F, Mba D, Gu F et al. An Investigation of Unsupervised Data-Driven Models for Internal Combustion Engine Condition Monitoring. In Zhang H, Feng G, Wang H, Gu F, Sinha JK, editors, Proceedings of IncoME-VI and TEPEN 2021 - Performance Engineering and Maintenance Engineering. Springer Science and Business Media B.V. 2023. p. 463-475. (Mechanisms and Machine Science). doi: 10.1007/978-3-030-99075-6_38

An Investigation of Unsupervised Data-Driven Models for Internal Combustion Engine Condition Monitoring

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