Research on Fault Diagnosis of Ship Power System Based on Improved Particle Swarm Optimization Neural Network Algorithm

被引：0
|
作者：
Yang, Ming [1 ]
Shi, Weifeng [1 ]
机构：
[1] Shanghai Maritime Univ, Logist Engn Coll, Shanghai, Peoples R China
来源：
PROCEEDINGS OF 2018 IEEE 3RD ADVANCED INFORMATION TECHNOLOGY, ELECTRONIC AND AUTOMATION CONTROL CONFERENCE (IAEAC 2018) | 2018年
关键词：
Ship Power System; Fault diagnosis; Improved Particle Swarm Optimization; particle dynamic optimization management; cross strategy;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
A fault diagnosis method for ship power system based on optimized particle swarm neural network is proposed. The optimization ability of particle swarm optimization is improved by particle dynamic optimization management and cross strategy. The threshold and weight of neural network are optimized by improved particle swarm optimization. The advantages of the algorithm is strong global search and fast convergence. It shows better speed and accuracy in the case of ship generator fault diagnosis.
引用
收藏
页码：108 / 113
页数：6
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