A neural network-based method for gas turbine blading fault diagnosis

International Journal of Modelling and Simulation

Volumn 21, Issue 1, 2001, Pages 51-60

  Angelakis, C ^a   Loukis, E N ^a   Pouliezos, A D ^a   Stavrakakis, G S ^a  

^a TECHNICAL UNIVERSITY OF CRETE   (Greece)

Author keywords

Fault diagnosis; Gas turbines; Neural network architectures

Indexed keywords

COMPUTER ARCHITECTURE; FAILURE ANALYSIS; GAS TURBINES; PATTERN RECOGNITION; QUANTUM THEORY; RADIAL BASIS FUNCTION NETWORKS; TURBOMACHINE BLADES;

FAULT DIAGNOSIS; GAS TURBINE BLADING; LEARNING VECTOR QUANTIZATION; MODULAR MULTILAYER PERCEPTRON; MULTILAYER PERCEPTRON; NEURAL NETWORK ARCHITECTURE;

NEURAL NETWORKS;

EID: 0035096249     PISSN: 02286203     EISSN: None     Source Type: Journal    
DOI: 10.1080/02286203.2001.11442186     Document Type: Article

References (12)

1. Combination of different unsteady quantity measurements for gas turbine blade fault diagnosis
2. Fault detection and diagnosis in gas turbines
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7. Orthogonal least squares learning algorithm for radial basis function networks