The Fault Diagnosis for Electro-Hydraulic Servo Valve Based on the Improved Genetic Neural Network Algorithm

Author

Fu, Lian-dong ; Chen, Kui-sheng ; Yu, Jun-sheng ; Zeng, Liang-Cai

Author_Institution

Coll. of Machinery & Autom., Wuhan Univ. of Sci. & Technol.

fYear

2006

fDate

13-16 Aug. 2006

Firstpage

2995

Lastpage

2999

Abstract

The paper analyzes the merits and drawbacks of the genetic algorithm and BP neural network, combines with the improved genetic algorithm and BP neural network to obtain a new algorithm. The new algorithm is used in the fault diagnosis of electro-hydraulic servo valve and justified its validity, accuracy and rapidity by experiment. The BP algorithm, the conventional GA-BP algorithm and the improved GA-BP algorithm are compared by the data of experiment. It is shown the superiority of the improved GA-BP algorithm in the fault diagnosis field

Keywords

backpropagation; electrohydraulic control equipment; fault diagnosis; genetic algorithms; servomechanisms; valves; BP neural network; electro-hydraulic servo valve; fault diagnosis; genetic neural network algorithm; Control systems; Convergence; Cost function; Cybernetics; Educational institutions; Fault diagnosis; Genetic algorithms; Machine learning; Neural networks; Servomechanisms; Telecommunication control; Valves; Electro-hydraulic servo valve; Fault diagnosis; Genetic algorithm; Neural network;

fLanguage

English

Publisher

ieee

Conference_Titel

Machine Learning and Cybernetics, 2006 International Conference on

Conference_Location

Dalian, China

Print_ISBN

1-4244-0061-9

Type

conf

DOI

10.1109/ICMLC.2006.259153

Filename

4028576