关键词: 飞机液压系统, 熵权法, 信息熵, 人工蜂群, 反向传播（BP）神经网络, 故障诊断

Abstract: In order to diagnose the faults of aircraft hydraulic system effectively, a method based on entropy weight and ABC-BP neural network is proposed, which is according to the signal of hydraulic system pressure. In this model，extraction of eigenvalues of aircraft hydraulic system pressure signal is the first step, and then, it calculates eigenvalue information entropy according to entropy weight method, the bigger of results as the input of the neural network, and in this paper, BP neural network is optimized by artificial bee colony through replacing the artificial bee colony fitness with the error function of BP neural network, finally, selecting the best fitness individual parameters as the weights and thresholds of the neural network ,this method not only reduces the input dimension of the model, but also improves the diagnostic accuracy.The simulation model of the landing gear retractable control system is established. The simulation results show that the diagnosis model has better fault diagnosis effect, and provides a new idea for the faults diagnosis of aircraft hydraulic system.

Key words: aircraft hydraulic system, entropy weight method, information entropy, artificial bee colony, Back Propagation（BP） neural network, fault diagnosis