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
Link To Document :
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