基于人工神经网络的液压振动系统研究 |
| |
引用本文: | 郭志刚,李文选,冯继刚.基于人工神经网络的液压振动系统研究[J].河北煤炭建筑工程学院学报,2012(2):78-80. |
| |
作者姓名: | 郭志刚 李文选 冯继刚 |
| |
作者单位: | 河北工程大学机电工程学院,河北邯郸056038 |
| |
摘 要: | 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。
|
关 键 词: | 正交试验 人工神经网络 数学模型 计算机仿真 |
Study on hydraulic vibration system based on artificial neural network |
| |
Affiliation: | GUO Zhi - gang , LI Wen - xuan , FENG Ji - gang (College of Mechanical and Electrical Engineering, Hebei University of Engineering, Hebei Handan 056038, China) |
| |
Abstract: | 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. |
| |
Keywords: | orthogonal test artificial neural network mathematical model computer simulation |
本文献已被 维普 等数据库收录! |