基于人工神经网络的液压振动系统研究

以两自由度液压激振压路机的液压振动系统为研究对象，采用立体正交试验选取试验因素，在每个试验因素中选择3个水平子集合，获得训练神经网络的样本。通过人工神经网络理论建立数学模型，借助Mtalab仿真计算出试验因素水平子集合最优组合参数。研究结果表明：通过建立人工神经网络数学模型，得出立体正交表的最优组合仿真目标值为0．5523，系统刚度为3．3N／mm，与试验目标值的相对误差为10．46％，满足工程要求。

Study on hydraulic vibration system based on artificial neural network

The hydraulic vibration system of two freedom hydraulic vibration roller was the research object in this paper. Three horizontal subsets were selected in every experimental factor which was ob- tained from the three -dimensional orthogonal experiment to obtain the samples of the training neural network. The mathematic model was built by artificial neural network theory and the optimum com- bined parameters of horizontal subsets were established by means of Mtalab simulation. The results show that target value of the optimum combined is 0. 552 3 and the stiffness of the system is 3.3 N/ mm through the artificial neural network mathematics model. This meets the project requirement because of the relative error of 10.46% between experimental results and experimental target value.