DocumentCode
2315878
Title
Application of a neural network in gas turbine control sensor fault detection
Author
Simani, S. ; Fantuzzi, C. ; Spina, P.R.
Author_Institution
Dipt. di Ingegneria, Ferrara Univ., Italy
Volume
1
fYear
1998
fDate
1-4 Sep 1998
Firstpage
182
Abstract
An application of a procedure using a neural network for the detection and isolation of faults modeled by step functions in input-output control sensors of a single shaft industrial gas turbine is presented. The real process is modeled as a linear dynamic system corrupted by stochastic additive noise. The diagnosis system involves dynamic observers and utilizes the neural network in order to classify observer residuals into fault classes
Keywords
fault diagnosis; gas turbines; multilayer perceptrons; observers; pattern classification; sensors; dynamic observers; gas turbine control sensor fault detection; input-output control sensors; linear dynamic system; step functions; stochastic additive noise; Electrical equipment industry; Fault detection; Gas detectors; Gas industry; Industrial control; Neural networks; Shafts; Stochastic resonance; Stochastic systems; Turbines;
fLanguage
English
Publisher
ieee
Conference_Titel
Control Applications, 1998. Proceedings of the 1998 IEEE International Conference on
Conference_Location
Trieste
Print_ISBN
0-7803-4104-X
Type
conf
DOI
10.1109/CCA.1998.728322
Filename
728322
Link To Document