Fault detection and identification for longwall machinery using SCADA Data

Bongers, Daniel R. and Gurgenci, Hal (2008). Fault detection and identification for longwall machinery using SCADA Data. In Khairy A.H. Kobbacy and D.N.Prabhakar Murthy (Ed.), Complex system maintenance handbook (pp. 611-641) London, U.K.: Springer. doi:10.1007/978-1-84800-011-7_25


Author Bongers, Daniel R.
Gurgenci, Hal
Title of chapter Fault detection and identification for longwall machinery using SCADA Data
Title of book Complex system maintenance handbook
Place of Publication London, U.K.
Publisher Springer
Publication Year 2008
Sub-type Research book chapter (original research)
DOI 10.1007/978-1-84800-011-7_25
Open Access Status
ISBN 9781848000100
1848000103
ISSN 2196-999X
Editor Khairy A.H. Kobbacy
D.N.Prabhakar Murthy
Volume number 8
Chapter number 25
Start page 611
End page 641
Total pages 31
Total chapters 25
Subjects B1
0913 Mechanical Engineering
970109 Expanding Knowledge in Engineering
Abstract/Summary Despite the most refined maintenance strategies, equipment failures do occur. The degree to which an industrial process or system is affected by these depends on the severity of the faults/failures, the time required to identify the faults and the time required to rectify the faults. Real-time fault detection and identification (FDI) offers maintenance personnel the ability to minimise, and potentially eliminate one or more of these factors, thereby facilitating greater equipment utilisation and increased system availability.
Keyword Fault detection and identification (FDI)
Equipment failures
Longwall machinery
Q-Index Code B1
Q-Index Status Confirmed Code
Additional Notes xi, 657 p. : ill. ; 25 cm.

 
Versions
Version Filter Type
Citation counts: Scopus Citation Count Cited 1 times in Scopus Article | Citations
Google Scholar Search Google Scholar
Created: Thu, 09 Apr 2009, 19:03:42 EST by Gail Smith on behalf of Faculty Of Engineering, Architecture & Info Tech