A Genetic Algorithm-based neural network approach for fault diagnosis in hydraulic servo-valves

作者:Huang Hao*; Chen Kuisheng; Zeng Liangcai
来源:ADVANCES IN MACHINE LEARNING AND CYBERNETICS, SPRINGER-VERLAG BERLIN, HEIDELBERGER PLATZ 3, D-14197 BERLIN, GERMANY, 813-821, 2006.

摘要

The hydraulic servo-valve is the key component of the electrohydraulic system. But it is difficult to diagnose faults in a hydraulic servo-valve. In this paper, a Genetic Algorithm-based Artificial Neural Network model for fault diagnosis in hydraulic servo-valves is proposed. We use a known set of servo-valve faults as the outputs to the valve-behavior model. Adoption of this approach brings about the advantages of reducing training time and increasing accuracy when compared with the traditional Back Propagation Neural Network.