Large Data and AI Analysis Based Online Diagnosis System Application of Steel Ladle Slewing Bearing

Wei Hu; Fengshou Gu; Shiqi Chen

doi:10.1007/978-3-030-57745-2_123

Large Data and AI Analysis Based Online Diagnosis System Application of Steel Ladle Slewing Bearing

Wei Hu, Fengshou Gu, Shiqi Chen

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

4 Citations (Scopus)

Abstract

Setting the default diagnosis and residual longevity of steel ladle turret bearing as the research subject, this article developed a large data and fusion of data mining with expert system based AI default diagnosis system, which has been successfully applicated in the default diagnosis of steel ladle turret bearing of a steel, saving tremendous time for steel mill’s decisive equipment maintenance by precisely predict the residual longevity of the equipment.

Original language	English
Title of host publication	Advances in Asset Management and Condition Monitoring, COMADEM 2019
Editors	Andrew Ball, Len Gelman, B.K.N. Rao
Publisher	Springer, Cham
Pages	1519-1527
Number of pages	9
Volume	166
ISBN (Electronic)	9783030577452
ISBN (Print)	9783030577445
DOIs	https://doi.org/10.1007/978-3-030-57745-2_123
Publication status	Published - 28 Aug 2020
Event	32nd International Congress and Exhibition on Conditioning Monitoring and Diagnostic Engineering Management Conference - University of Huddersfield, Huddersfield, United Kingdom Duration: 3 Sept 2019 → 5 Sept 2019 Conference number: 32 http://www.comadem2019.com/ (Link to Conference Website)

Publication series

Name	Smart Innovation, Systems and Technologies
Publisher	Springer
Volume	166
ISSN (Print)	2190-3018
ISSN (Electronic)	2190-3026

Conference

Conference	32nd International Congress and Exhibition on Conditioning Monitoring and Diagnostic Engineering Management Conference
Abbreviated title	COMADEM 2019
Country/Territory	United Kingdom
City	Huddersfield
Period	3/09/19 → 5/09/19
Internet address	http://www.comadem2019.com/ (Link to Conference Website)

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10.1007/978-3-030-57745-2_123Licence: Unspecified

Cite this

Hu, W., Gu, F., & Chen, S. (2020). Large Data and AI Analysis Based Online Diagnosis System Application of Steel Ladle Slewing Bearing. In A. Ball, L. Gelman, & B. K. N. Rao (Eds.), Advances in Asset Management and Condition Monitoring, COMADEM 2019 (Vol. 166, pp. 1519-1527). (Smart Innovation, Systems and Technologies; Vol. 166). Springer, Cham. https://doi.org/10.1007/978-3-030-57745-2_123

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title = "Large Data and AI Analysis Based Online Diagnosis System Application of Steel Ladle Slewing Bearing",

abstract = "Setting the default diagnosis and residual longevity of steel ladle turret bearing as the research subject, this article developed a large data and fusion of data mining with expert system based AI default diagnosis system, which has been successfully applicated in the default diagnosis of steel ladle turret bearing of a steel, saving tremendous time for steel mill{\textquoteright}s decisive equipment maintenance by precisely predict the residual longevity of the equipment.",

keywords = "Fault diagnosis, Residual life prediction, Slewing bearing",

author = "Wei Hu and Fengshou Gu and Shiqi Chen",

year = "2020",

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doi = "10.1007/978-3-030-57745-2_123",

language = "English",

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volume = "166",

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editor = "Andrew Ball and Len Gelman and B.K.N. Rao",

booktitle = "Advances in Asset Management and Condition Monitoring, COMADEM 2019",

address = "Switzerland",

note = "32nd International Congress and Exhibition on Conditioning Monitoring and Diagnostic Engineering Management Conference, COMADEM 2019 ; Conference date: 03-09-2019 Through 05-09-2019",

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Hu, W, Gu, F & Chen, S 2020, Large Data and AI Analysis Based Online Diagnosis System Application of Steel Ladle Slewing Bearing. in A Ball, L Gelman & BKN Rao (eds), Advances in Asset Management and Condition Monitoring, COMADEM 2019. vol. 166, Smart Innovation, Systems and Technologies, vol. 166, Springer, Cham, pp. 1519-1527, 32nd International Congress and Exhibition on Conditioning Monitoring and Diagnostic Engineering Management Conference, Huddersfield, United Kingdom, 3/09/19. https://doi.org/10.1007/978-3-030-57745-2_123

Large Data and AI Analysis Based Online Diagnosis System Application of Steel Ladle Slewing Bearing. / Hu, Wei; Gu, Fengshou; Chen, Shiqi.
Advances in Asset Management and Condition Monitoring, COMADEM 2019. ed. / Andrew Ball; Len Gelman; B.K.N. Rao. Vol. 166 Springer, Cham, 2020. p. 1519-1527 (Smart Innovation, Systems and Technologies; Vol. 166).

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

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T1 - Large Data and AI Analysis Based Online Diagnosis System Application of Steel Ladle Slewing Bearing

AU - Hu, Wei

AU - Gu, Fengshou

AU - Chen, Shiqi

N1 - Conference code: 32

PY - 2020/8/28

Y1 - 2020/8/28

N2 - Setting the default diagnosis and residual longevity of steel ladle turret bearing as the research subject, this article developed a large data and fusion of data mining with expert system based AI default diagnosis system, which has been successfully applicated in the default diagnosis of steel ladle turret bearing of a steel, saving tremendous time for steel mill’s decisive equipment maintenance by precisely predict the residual longevity of the equipment.

AB - Setting the default diagnosis and residual longevity of steel ladle turret bearing as the research subject, this article developed a large data and fusion of data mining with expert system based AI default diagnosis system, which has been successfully applicated in the default diagnosis of steel ladle turret bearing of a steel, saving tremendous time for steel mill’s decisive equipment maintenance by precisely predict the residual longevity of the equipment.

KW - Fault diagnosis

KW - Residual life prediction

KW - Slewing bearing

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U2 - 10.1007/978-3-030-57745-2_123

DO - 10.1007/978-3-030-57745-2_123

M3 - Conference contribution

AN - SCOPUS:85091277185

SN - 9783030577445

VL - 166

T3 - Smart Innovation, Systems and Technologies

SP - 1519

EP - 1527

BT - Advances in Asset Management and Condition Monitoring, COMADEM 2019

A2 - Ball, Andrew

A2 - Gelman, Len

A2 - Rao, B.K.N.

PB - Springer, Cham

T2 - 32nd International Congress and Exhibition on Conditioning Monitoring and Diagnostic Engineering Management Conference

Y2 - 3 September 2019 through 5 September 2019

ER -

Hu W, Gu F, Chen S. Large Data and AI Analysis Based Online Diagnosis System Application of Steel Ladle Slewing Bearing. In Ball A, Gelman L, Rao BKN, editors, Advances in Asset Management and Condition Monitoring, COMADEM 2019. Vol. 166. Springer, Cham. 2020. p. 1519-1527. (Smart Innovation, Systems and Technologies). Epub 2020 Aug 28. doi: 10.1007/978-3-030-57745-2_123

Large Data and AI Analysis Based Online Diagnosis System Application of Steel Ladle Slewing Bearing

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