DocumentCode
438884
Title
Proactive health management for automated equipment: from diagnostics to prognostics
Author
Zhang, D.H. ; Zhang, J.B. ; Luo, M. ; Zhao, Y.Z. ; Wong, M.M.
Author_Institution
Singapore Inst. of Manufacturing Technol., Nanyang, Singapore
Volume
1
fYear
2004
fDate
6-9 Dec. 2004
Firstpage
479
Abstract
In this paper, generic methodologies for prognostic machinery health management are discussed and a framework is proposed for extending prognostic capabilities to conventional maintenance and diagnostic system (MDS). Two specific techniques that can be used to extract knowledge and rules for fault prediction are discussed. These techniques are based on the analysis of historical data gathered by the MDS. The paper further elaborates on knowledge based real-time failure prediction and recommends a diagnostics-to-prognostics approach that enables traditional reactive MDS to be transformed into proactive health management (PHM) systems.
Keywords
condition monitoring; fault diagnosis; knowledge acquisition; machinery; mechanical engineering computing; preventive maintenance; real-time systems; automated equipment; diagnostics-to-prognostics approach; fault prediction; knowledge based real-time failure prediction; knowledge extraction; maintenance and diagnostic system; proactive health management systems; prognostic machinery health management; Computerized monitoring; Condition monitoring; Data mining; Fault detection; Intelligent sensors; Knowledge management; Machinery; Maintenance; Military computing; Technology management;
fLanguage
English
Publisher
ieee
Conference_Titel
Control, Automation, Robotics and Vision Conference, 2004. ICARCV 2004 8th
Print_ISBN
0-7803-8653-1
Type
conf
DOI
10.1109/ICARCV.2004.1468872
Filename
1468872
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