An application of genetic neural networks in fault diagnosis of aero-engine vibration

This paper presents a hybrid method named genetic neural networks(GNN) which combines genetic algorithm(GA) with neural networks(NN). Fault diagnostic results of aero-engine vibration based on GNN are obtained by setting typical vibration fault modes, including rotor imbalance, rotor disalignment and looseness of rotors. It is shown that this method is superior to the traditional neural network in improving the accuracy and rapidity of vibration fault diagnosis.