DocumentCode
436318
Title
Fault detection in fossil electric power plant via neural networks
Author
Sanchez, Edgar N. ; Suarez, D.A. ; Ruz, J.A.
Volume
17
fYear
2004
fDate
June 28 2004-July 1 2004
Firstpage
213
Lastpage
218
Abstract
In this paper, the authors discuss fault detection for fossil electric power plants. It is intended to use recurrent neural networks to perform such a detection. A sceme for fault detection is proposed. This scheme is based on comparison bctween thc measures coming from the plant and thc predicted values generatcd by a neural network model. This research is in its beginning: right now a full scale simulator is being uscd to generate the required data base.
Keywords
Costs; Electrical fault detection; Fault diagnosis; Filtering; Intelligent networks; Kalman filters; Large Hadron Collider; Monitoring; Neural networks; Robustness;
fLanguage
English
Publisher
ieee
Conference_Titel
Automation Congress, 2004. Proceedings. World
Conference_Location
Seville
Print_ISBN
1-889335-21-5
Type
conf
Filename
1439370
Link To Document