Fault Diagnosis Based on Multi-layer Structure Wavelet Neural Networks in Attitude Heading Reference System

被引：2

作者：

Jiao, Zhun ^{[1
]}

Zhang, Rong ^{[1
]}

机构：

[1] First Aviat Coll Air Force, Xin Yang, Peoples R China

来源：

ADVANCED DEVELOPMENT OF ENGINEERING SCIENCE IV | 2014年 / 1046卷

关键词：

Attitude Heading Reference System (AHRS); Multiple Wavelet neural network (MWNN); Fault Diagnosis;

D O I：

10.4028/www.scientific.net/AMR.1046.270

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

According to the structure feature of aircraft's attitude heading reference system and procedure of fault diagnosis, this paper sets up multi-layer neural network model structure for fault diagnosis of complex equipment, and applies the model to the fault diagnosis of attitude heading reference system in aircraft. The conclusion is that the method can effectively reduce the complexity of fault diagnosis for complex system, and imp rove diagnosis rate and efficiency of attitude heading reference system. At the same time, it also provides a new method and theory to diagnosis the non-linear system.

引用

页码：270 / 274

页数：5