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针对提升机液压站故障特性,以小波神经网络为工具建立了其故障预测模型。介绍了小波神经网络的结构、算法以及训练流程。分析了影响液压站故障因素,建立了其预测模型。在MATLAB环境下对网络进行训练。实验表明,该模型具有收敛速度快,预测精度高的特点,能够满足实际要求。
Aiming at the failure characteristics of hoist hydraulic station, the fault prediction model was established by using wavelet neural network as a tool. The structure, algorithm and training flow of wavelet neural network are introduced. The factors affecting the failure of the hydraulic station are analyzed and its prediction model is established. In the MATLAB environment for network training. Experiments show that the model has the characteristics of fast convergence and high prediction accuracy, which can meet the actual requirements.