An Application of Genetic Neural Networks in Fault Diagnosis of Aero-engine Vibration

被引：0

作者：

Zhang, Fengling ^{[1
]}

Wang, Zhi ^{[1
]}

机构：

[1] Shenyang Aerosp Univ, Coll Aerosp Engn, Shenyang, Peoples R China

来源：

2013 NINTH INTERNATIONAL CONFERENCE ON NATURAL COMPUTATION (ICNC) | 2013年

关键词：

genetic neural networks; genetic algorithm; neural networks; aero-engine vibration; fault diagnosis;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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.

引用

页码：116 / 121

页数：6

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