DocumentCode :
264332
Title :
Development of asset fault signatures for Prognostic and Health Management in the nuclear industry
Author :
Agarwal, Vivek ; Lybeck, Nancy J. ; Bickford, Randall ; Rusaw, Richard
Author_Institution :
Dept. of Human Factors, Idaho Nat. Lab., Idaho Falls, ID, USA
fYear :
2014
fDate :
22-25 June 2014
Firstpage :
1
Lastpage :
7
Abstract :
Proactive online monitoring in the nuclear industry is being explored using the Electric Power Research Institute´s Fleet-Wide Prognostic and Health Management (FW-PHM) Suite software. The FW-PHM Suite is a set of web-based diagnostic and prognostic tools and databases that serves as an integrated health monitoring architecture. The FW-PHM Suite has four main modules: (1) Diagnostic Advisor, (2) Asset Fault Signature Database, (3) Remaining Useful Life Advisor, and (4) Remaining Useful Life Database. This paper focuses on development of asset fault signatures to assess the health status of generator step-up generators and emergency diesel generators in nuclear power plants. Asset fault signatures describe distinctive features based on technical examinations that can be used to detect a specific fault type. At the most basic level, fault signatures are comprised of an asset type, a fault type, and a set of one or more fault features (symptoms) that are indicative of the specified fault. The Asset Fault Signature Database is populated with asset fault signatures via a content development exercise that is based on the results of intensive technical research and on the knowledge and experience of technical experts. The developed fault signatures capture this knowledge and implement it in a standardized approach, thereby streamlining the diagnostic and prognostic process. This will support the automation of proactive online monitoring techniques in nuclear power plants to diagnose incipient faults, perform proactive maintenance, and estimate the remaining useful life of assets.
Keywords :
Internet; condition monitoring; diesel-electric generators; fault diagnosis; knowledge management; maintenance engineering; nuclear power; nuclear power stations; power engineering computing; remaining life assessment; Electric Power Research Institute; FW-PHM Suite software; Fleet-Wide Prognostic and Health Management Suite software; Web-based diagnostic and prognostic tool; asset fault signature database; asset type; content development exercise; diagnostic advisor; emergency diesel generators; fault feature; health status assessment; incipient fault diagnosis; integrated health monitoring architecture; nuclear industry; nuclear power plants; proactive maintenance; proactive online monitoring; remaining useful life advisor; remaining useful life database; specific fault type detection; step-up generators; technical examination; technical expert knowledge; Databases; Degradation; Generators; Insulation; Monitoring; Prognostics and health management; Windings; asset fault signatures; emergency diesel generators; fleet-wide monitoring; generator step-up transformers;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Prognostics and Health Management (PHM), 2014 IEEE Conference on
Conference_Location :
Cheney, WA
Type :
conf
DOI :
10.1109/ICPHM.2014.7036366
Filename :
7036366
Link To Document :
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