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
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;
Conference_Titel :
Control Applications, 1998. Proceedings of the 1998 IEEE International Conference on
Conference_Location :
Trieste
Print_ISBN :
0-7803-4104-X
DOI :
10.1109/CCA.1998.728322
