DocumentCode
231397
Title
Fault identification for the large-scale system using trend analysis
Author
Gu Xiaodan ; Deng Fang ; Chen Jie
Author_Institution
Sch. of Autom., Beijing Inst. of Technol., Beijing, China
fYear
2014
fDate
28-30 July 2014
Firstpage
3301
Lastpage
3306
Abstract
Fault identification for large-scale system differs from fault identification for the respective device, which is more complicated with higher real-time requirements. While trend analysis is a simple, rapid and widely applied trend modeling method, it is one of good solutions. In this paper, we summarize achievements on the methods of trend extraction and similarity measure for trends matching. We suggest a framework of fault identification for the large-scale system using trend analysis, and the development of an optimal and robust faults-base for the large-scale system is also interpreted.
Keywords
fault diagnosis; feature extraction; identification; large-scale systems; fault identification; large-scale system; robust fault-base; signal trends; similarity measure method; trend analysis; trend extraction method; trend modeling method; trends matching; Decision support systems; fault identification; faults-base; large-scale system; trend analysis;
fLanguage
English
Publisher
ieee
Conference_Titel
Control Conference (CCC), 2014 33rd Chinese
Conference_Location
Nanjing
Type
conf
DOI
10.1109/ChiCC.2014.6895485
Filename
6895485
Link To Document