DocumentCode
2572373
Title
Neural networks in fault detection: a case study
Author
Hush, D.R. ; Abdallah, C.T. ; Heileman, G.L. ; Docampo, D.
Author_Institution
Dept. of Electr. Eng. & Comput. Eng., New Mexico Univ., Albuquerque, NM, USA
Volume
2
fYear
1997
fDate
4-6 Jun 1997
Firstpage
918
Abstract
We study the applications of neural nets in the area of fault detection in real vibrational data. The study is one of the first to include a large set of real vibrational data and to illustrate the potential as well as the limitations of neural networks for fault detection
Keywords
ART neural nets; computerised monitoring; fault diagnosis; feature extraction; feedforward neural nets; fuzzy neural nets; multilayer perceptrons; pattern classification; signal processing; fault detection; neural networks; vibrational data; Computer aided software engineering; Fault detection; Helicopters; Intelligent networks; Monitoring; Neural networks; Potential well; Shafts; Signal processing algorithms; Subspace constraints;
fLanguage
English
Publisher
ieee
Conference_Titel
American Control Conference, 1997. Proceedings of the 1997
Conference_Location
Albuquerque, NM
ISSN
0743-1619
Print_ISBN
0-7803-3832-4
Type
conf
DOI
10.1109/ACC.1997.609660
Filename
609660
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