Title :
BP neural network-based on fault diagnosis of hydraulic servo-valves
Author :
Huang, Hao ; Chen, Kui-sheng ; Zeng, Liang-Cai
Author_Institution :
Coll. of Machinery & Autom., Wuhan Univ. of Sci. & Technol., China
Abstract :
This paper presents a new approach for fault diagnosis of hydraulic servo-valves with the BP neural network based on genetic algorithm. The paper uses a known set of faults as the output to the valve-behavior model. An appropriate neural network is established to be the best solution to the problem. Adoption of this approach brings about advantages of shortening training time and high-accuracy when compared with other artificial neural network.
Keywords :
backpropagation; fault diagnosis; genetic algorithms; hydraulic systems; neural nets; servomechanisms; valves; artificial neural network; backpropagation neural network; fault diagnosis; genetic algorithm; hydraulic servovalves; valve behavior model; Artificial neural networks; Automation; Biological cells; Educational institutions; Electronic mail; Fault diagnosis; Genetic algorithms; Machinery; Neural networks; Servomechanisms; BP Neural network; fault diagnosis; genetic algorithm; hydraulic servo-valve;
Conference_Titel :
Machine Learning and Cybernetics, 2005. Proceedings of 2005 International Conference on
Conference_Location :
Guangzhou, China
Print_ISBN :
0-7803-9091-1
DOI :
10.1109/ICMLC.2005.1527655
