Fault Diagnosis of Tolerance Analog Circuit Based on Wavelet Neural Network with PSO Algorithm

被引:3
|
作者
Cong, Wei [1 ]
Jing, Bo [1 ]
Yu, Hong-Kun [1 ]
机构
[1] Air Force Engn Univ, Aeronaut & Astronaut Engn Coll, Xian 710038, Shaanxi, Peoples R China
来源
MECHATRONICS AND COMPUTATIONAL MECHANICS | 2013年 / 307卷
关键词
Wavelet neural network; Particle swarm optimization; Velocity disturbance operator; Fault diagnosis;
D O I
10.4028/www.scientific.net/AMM.307.312
中图分类号
TH [机械、仪表工业];
学科分类号
0802 ;
摘要
For the Difficulties in fault diagnosis of tolerance analog circuit, a Wavelet Neural Network (WNN) diagnosis method based on Particle Swarm Optimization (PSO) algorithm is proposed. To overcome the deficiencies of the traditional BP algorithm using in WNN, PSO algorithm is introduced into the parameters optimization in WNN, and the velocity disturbance operator is embedded to ensure the particle out of the premature position for PSO algorithm performance. The simulation results show that the proposed method has the fast training rate, accurate diagnosis, without local convergence.
引用
收藏
页码:312 / 315
页数:4
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