海军航空工程学院学报2011，Vol.26Issue(2)：131-135,5.
PSO-RBF神经网络在舵机系统故障诊断中的应用
Application of RBF Neural Network Based on PSO Algorithm in Fault Diagnosis of Actuation System
史贤俊 1张文广 1张艳 2张树团1
作者信息
- 1. 海军航空工程学院控制工程系,山东烟台264001
- 2. 海军驻上海地区航天系统军事代表室,上海200090
- 折叠
摘要
Abstract
In this paper, the failure observer based on RBF neural network was developed, and a two-level learning method for designing radial basis function (RBF) network based on particle swarm optimization (PSO)and regularized orthogonal least squares (ROLS) was proposed. Finally, the RBF observer was applied to fault diagnosis of the missile's actuation system. The experimental results showed that the failure observer based on the RBF neural network was effective in detecting the failure of the missile's actuation system.关键词
RBF神经网络/正交最小二乘法/粒子群优化算法/故障诊断Key words
RBF neural network/ orthogonal least squares algorithm/ particle swarm optimization/ fault diagnosis分类
信息技术与安全科学引用本文复制引用
史贤俊,张文广,张艳,张树团..PSO-RBF神经网络在舵机系统故障诊断中的应用[J].海军航空工程学院学报,2011,26(2):131-135,5.
