Research on Fault Diagnosis of Fork Lift Truck Hydraulic System Based on Artificial Neural Network

Author

Li, Heqing ; Tan, Qing

Author_Institution

Sch. of Automobile & Mech. Eng., Changsha Univ. of Sci. & Technol., Changsha, China

Volume

1

fYear

2009

fDate

11-12 April 2009

Firstpage

697

Lastpage

699

Abstract

The structure and algorithm of BP neural net were described, the realization process of the fault diagnosis of hydraulic system based on BP neural net was discussed. According to the experiment and test of fault of fork lift truck hydraulic system, the BP net has better learning function, high net convergence rate and high stability of learning and memory. The diagnosis results indicate that the presented diagnosis method has high reliability and can attain the expected results, which can be applied to fault diagnosis of hydraulic system.

Keywords

artificial intelligence; fork lift trucks; hydraulic systems; maintenance engineering; mechanical engineering computing; neural nets; BP neural net; artificial neural network; fault diagnosis; fork lift truck hydraulic system; maintenance method; realization process; Artificial neural networks; Automation; Automobiles; Fault diagnosis; Hydraulic systems; Maintenance; Mechanical variables measurement; Mechatronics; Neural networks; Neurons; Bp algorithm; Neural network; fault diagnosis; hydraulic system;

fLanguage

English

Publisher

ieee

Conference_Titel

Measuring Technology and Mechatronics Automation, 2009. ICMTMA '09. International Conference on

Conference_Location

Zhangjiajie, Hunan

Print_ISBN

978-0-7695-3583-8

Type

conf

DOI

10.1109/ICMTMA.2009.290

Filename

5203068