Engine Fault Diagnosis Based on PSO-BP Network

被引：0

作者：

Nie, Lixin ^{[1
]}

Zhang, Tianxia ^{[1
]}

Wang, Shuju ^{[1
]}

Zhang, Liping ^{[1
]}

机构：

[1] Northeastern Univ, Dept Mech Engn & Automat, Shenyang 110004, Peoples R China

来源：

MATERIALS AND MANUFACTURING, PTS 1 AND 2 | 2011年 / 299-300卷

关键词：

Fault Diagnosis; PSO (Particle Swarm Optimization); BP Network; Inertia Weight; Premature Convergence;

D O I：

10.4028/www.scientific.net/AMR.299-300.1307

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

BP network could deal with some nonlinear problems such as fault diagnosis, but the gradient-based method tends to get stuck in local optima or premature convergence. As a population-based heuristic optimization algorithm, PSO method could increase training accuracy of BP network so as to improve discriminant precision of fault diagnosis of equipment such as engine. Ladder diminishing inertia weights tend to improve network's convergence precision and efficiency during the late stage of PSO iterations, in addition, LPSO or RegPSO contributes to confining premature convergence. The PSO-BP fault diagnosis model of 190A diesel engine has verified the above opinions.

引用

页码：1307 / 1311

页数：5

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