摘要
建立了一种智能预测控制系统。该系统根据各磨削阶段的特点,在不同阶段分别采用不同的优化控制策略:粗磨阶段,采用在烧伤极限内大进给和变速磨削优化策略;精磨阶段,采用由神经网络预测、模糊逻辑控制的工件尺寸智能优化方法;光磨阶段,采用工件表面粗糙度模糊神经网络预测辨识控制方法。基于神经网络的专家系统,提供各阶段初始磨削加工参数。实验结果表明,该系统在外圆磨削加工中适应性强,可极大地提高磨削质量和效率。
An intelligent prediction control system was built. Optimization control strategy was changed in the different grinding stage. Deep -feed within the limit of burn and variety velocity grinding were adopted during the rough grinding stage; the prediction neural network and the fuzzy logic controller was used to optimize and control the workpiece size during the fine grinding stage; two fuzzy - neural networks were used to predict and control workpiece surface roughness during spark - out stage. The expert system based on neural network provides the initial grinding parameters for these grinding stages. Experimental results show that this intelligent pre diction control system is feasible and has high adaptive capability.
出处
《机床与液压》
北大核心
2006年第7期38-41,46,共5页
Machine Tool & Hydraulics
基金
吉林省科技发展计划资助项目(20020632)
关键词
外圆磨削
预测控制
神经网络
模糊逻辑
模糊神经网络
专家系统
变速磨削
External cylindrical grinding
Prediction control
Neural network
Fuzzy logic
Fuzzy- neural networks
Expert system
Variety velocity grinding
