Title : 
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
         
        
        
        
        
        
        
            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;
         
        
        
        
            Conference_Titel : 
Measuring Technology and Mechatronics Automation, 2009. ICMTMA '09. International Conference on
         
        
            Conference_Location : 
Zhangjiajie, Hunan
         
        
            Print_ISBN : 
978-0-7695-3583-8
         
        
        
            DOI : 
10.1109/ICMTMA.2009.290