Fault monitoring and diagnosis in mining equipment: Current and future developments

Joseph Sottile; Lawrence E. Holloway

doi:10.1109/IAS.1992.244201

Fault monitoring and diagnosis in mining equipment: Current and future developments

Joseph Sottile, Lawrence E. Holloway

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

2 Scopus citations

Abstract

Proper detection and diagnosis of failing system components is crucial to efficient mining operations. However, the harsh mining environment offers special challenges to these types of actions. The atmosphere is damp, dirty, and potentially explosive, and equipment is located in confined areas far from shop facilities. These conditions, coupled with the increasing cost of downtime and complexity of mining equipment, have forced researchers and operators to investigate alternatives for improving equipment maintainability. This paper surveys monitoring and diagnosis technologies which offer opportunities for improving equipment availability in mining. Expert systems, model-based approaches, and neural nets are each discussed in the context of fault detection and diagnosis. The paper concludes with a comparative discussion summarizing the advantages and disadvantages of each.

Original language	English
Title of host publication	Conference Record of the 1992 IEEE Industry Applications Society Annual Meeting, IAS 1992
Pages	2026-2033
Number of pages	8
ISBN (Electronic)	078030635X
DOIs	https://doi.org/10.1109/IAS.1992.244201
State	Published - 1992
Event	1992 IEEE Industry Applications Society Annual Meeting, IAS 1992 - Houston, United States Duration: Oct 4 1992 → Oct 9 1992

Publication series

Name	Conference Record - IAS Annual Meeting (IEEE Industry Applications Society)
Volume	1992-January
ISSN (Print)	0197-2618

Conference

Conference	1992 IEEE Industry Applications Society Annual Meeting, IAS 1992
Country/Territory	United States
City	Houston
Period	10/4/92 → 10/9/92

Bibliographical note

Publisher Copyright:
© IEEE.

ASJC Scopus subject areas

Control and Systems Engineering
Industrial and Manufacturing Engineering
Electrical and Electronic Engineering

Access to Document

10.1109/IAS.1992.244201

Cite this

Sottile, J., & Holloway, L. E. (1992). Fault monitoring and diagnosis in mining equipment: Current and future developments. In Conference Record of the 1992 IEEE Industry Applications Society Annual Meeting, IAS 1992 (pp. 2026-2033). Article 244201 (Conference Record - IAS Annual Meeting (IEEE Industry Applications Society); Vol. 1992-January). https://doi.org/10.1109/IAS.1992.244201

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title = "Fault monitoring and diagnosis in mining equipment: Current and future developments",

abstract = "Proper detection and diagnosis of failing system components is crucial to efficient mining operations. However, the harsh mining environment offers special challenges to these types of actions. The atmosphere is damp, dirty, and potentially explosive, and equipment is located in confined areas far from shop facilities. These conditions, coupled with the increasing cost of downtime and complexity of mining equipment, have forced researchers and operators to investigate alternatives for improving equipment maintainability. This paper surveys monitoring and diagnosis technologies which offer opportunities for improving equipment availability in mining. Expert systems, model-based approaches, and neural nets are each discussed in the context of fault detection and diagnosis. The paper concludes with a comparative discussion summarizing the advantages and disadvantages of each.",

author = "Joseph Sottile and Holloway, {Lawrence E.}",

note = "Publisher Copyright: {\textcopyright} IEEE.; 1992 IEEE Industry Applications Society Annual Meeting, IAS 1992 ; Conference date: 04-10-1992 Through 09-10-1992",

year = "1992",

doi = "10.1109/IAS.1992.244201",

language = "English",

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Sottile, J & Holloway, LE 1992, Fault monitoring and diagnosis in mining equipment: Current and future developments. in Conference Record of the 1992 IEEE Industry Applications Society Annual Meeting, IAS 1992., 244201, Conference Record - IAS Annual Meeting (IEEE Industry Applications Society), vol. 1992-January, pp. 2026-2033, 1992 IEEE Industry Applications Society Annual Meeting, IAS 1992, Houston, United States, 10/4/92. https://doi.org/10.1109/IAS.1992.244201

Fault monitoring and diagnosis in mining equipment: Current and future developments. / Sottile, Joseph ; Holloway, Lawrence E.
Conference Record of the 1992 IEEE Industry Applications Society Annual Meeting, IAS 1992. 1992. p. 2026-2033 244201 (Conference Record - IAS Annual Meeting (IEEE Industry Applications Society); Vol. 1992-January).

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

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AB - Proper detection and diagnosis of failing system components is crucial to efficient mining operations. However, the harsh mining environment offers special challenges to these types of actions. The atmosphere is damp, dirty, and potentially explosive, and equipment is located in confined areas far from shop facilities. These conditions, coupled with the increasing cost of downtime and complexity of mining equipment, have forced researchers and operators to investigate alternatives for improving equipment maintainability. This paper surveys monitoring and diagnosis technologies which offer opportunities for improving equipment availability in mining. Expert systems, model-based approaches, and neural nets are each discussed in the context of fault detection and diagnosis. The paper concludes with a comparative discussion summarizing the advantages and disadvantages of each.

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Fault monitoring and diagnosis in mining equipment: Current and future developments

Abstract

Publication series

Conference

Bibliographical note

ASJC Scopus subject areas

Access to Document

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