电子束焊熔深神经网络模糊控制系统建模与仿真  

Modeling and Simulation of Fuzzy Neural Network Control System of Penetration in Titanium-alloy Electron Beam Welding

作　　者：石铭霄[1] 张秉刚[2] 陈国庆[2] 冯吉才[2] 樊丁[1] 

机构地区：[1]兰州理工大学甘肃省有色金属新材料重点实验室,兰州730050 [2]哈尔滨工业大学先进焊接与连接国家重点实验室,哈尔滨150001

出　　处：《机械工程学报》2012年第10期28-32,共5页Journal of Mechanical Engineering

基　　金：国家重点基础研究发展计划资助项目(973计划;2010CB731704)

摘　　要：研究钛合金电子束焊熔深控制系统建模问题。在分析电子束焊接特点的基础上,设计三因素五水平正交试验,通过试验得到不同焊接参数下熔宽和熔深的值,将熔宽和熔深的值作为训练样本对神经网络进行训练,建立以熔宽为输入,以熔深为输出的误差反向传播(Error back propagation,BP)神经网络模型,该模型由一个S型函数隐含层加上一个线性输出层组成。针对熔深数学模型难以获得的情况,设计以熔深的偏差和偏差变化率为输入变量,焊接电流的变化量为输出变量的模糊控制器,该控制器有9条模糊控制规则。将BP神经网络模型和模糊控制器结合起来建立钛合金电子束焊熔深控制系统模型,并且采用单位阶跃信号对该模型进行仿真试验,试验结果表明所设计的控制系统动态性能和稳态性能良好。The control system modeling of penetration is studied in titanium-alloy electron beam welding.On the basis of analysing the characteristics of electron beam welding,the orthogonal test of three factors and five levels is designed,the test is done to obtain the values of molten width and penetration under different welding parameters,the values of molten width and penetration are used as the training sample to train the neural network,thus a BP neural network model between molten width and penetration is established,the molten width is input,the penetration is output.The model consists of a S-function hidden layer plus a linear output layer.Because the mathematical model for penetration is difficult to obtain,so the fuzzy controller is designed,its input variables are bias and change rate of bias,its output variables are the change of welding current,The controller has nine fuzzy-control rules.The BP neural network model and fuzzy controller are combined to establish fuzzy neural network control-system model of penetration of titanium-alloy electron beam welding,and unit step signal is used to carry out the simulation experiment of the model,the results show that the dynamic performance and steady-state performance of designed control system are eminent.

关 键 词：电子束焊 神经网络 模糊控制 

分 类 号：TG456[金属学及工艺—焊接]