BP Network Optimized with Genetic Algorithm and Apply on The Fault Diagnose of Complex Equipment

Author

Meng, Xianyao ; Han, Xinjie ; Xu, Qingyang

Author_Institution

Dalian Maritime Univ., Dalian

fYear

2007

fDate

May 30 2007-June 1 2007

Firstpage

1630

Lastpage

1633

Abstract

The BP neural network has been widely applied on fault diagnose. The BP network adopt the arithmetic of searching along the grads drop, therefore there are some problems such as slow rate of convergence and easily getting into local infinitesimal. The genetic algorithm has excellence of rapid searching rate. Therefore, auto-adapt genetic algorithm is adopted to optimize the BP algorithms in the paper. For example, for fault diagnose in shafting of main engine, an ideal effect can be got while adopting BP network which had been optimized by genetic algorithms for the complex equipment.

Keywords

backpropagation; engines; fault diagnosis; genetic algorithms; neural nets; search problems; auto-adapt genetic algorithm; backpropagation neural network optimisation; complex equipment; fault diagnosis; main engine shafting; searching arithmetic; Arithmetic; Automatic control; Automation; Convergence; Engines; Evolution (biology); Fault diagnosis; Genetic algorithms; Neural networks; Testing; BP network; complex equipment; fault diagnose; genetic algorithm;

fLanguage

English

Publisher

ieee

Conference_Titel

Control and Automation, 2007. ICCA 2007. IEEE International Conference on

Conference_Location

Guangzhou

Print_ISBN

978-1-4244-0818-4

Electronic_ISBN

978-1-4244-0818-4

Type

conf

DOI

10.1109/ICCA.2007.4376636

Filename

4376636