Study of Method on Genetic BP Networks for Vibration Fault Diagnosis of Turbogenerator

被引：1

作者：

Zhang, Enping ^{[1
]}

Zhang, Huifen ^{[1
]}

Xue, Bicui ^{[1
]}

机构：

[1] Univ Jinan, Sch Elect Engn, Jinan, Shandong, Peoples R China

来源：

INTELLIGENT SYSTEM AND APPLIED MATERIAL, PTS 1 AND 2 | 2012年 / 466-467卷

关键词：

Genetic algorithm; neural network; faults;

D O I：

10.4028/www.scientific.net/AMR.466-467.1025

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Considering the complexity and relevance of fault diagnosis for turbo-generator, the paper makes diagnosis by adopting improved genetic BP network algorithm. In order to solve the problems of slow network learning and tendency of minimum point in BP algorithm, the structure and specific parameter of BP network optimized by genetic algorithm were used in the discussion of a model integrated with adaptive genetic neural algorithm, which was applied in the fault identification of turbo-generator. Experimental data shows that the algorithm is characterized by high convergence rate, effective vibration fault diagnosis for turbo-generator and relative high reliability and practicability.

引用

页码：1025 / 1030

页数：6