Title :
Fault detection in fossil electric power plant via neural networks
Author :
Sanchez, Edgar N. ; Suarez, D.A. ; Ruz, J.A.
fDate :
June 28 2004-July 1 2004
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;
Conference_Titel :
Automation Congress, 2004. Proceedings. World
Conference_Location :
Seville
Print_ISBN :
1-889335-21-5
