铣削加工表面粗糙度的智能预测  

Intelligent Prediction for Surface Roughness in Milling

作　　者：王凯[1] 

机构地区：[1]河北工程大学机电学院,河北邯郸056038

出　　处：《机床与液压》2009年第10期58-59,119,共3页Machine Tool & Hydraulics

摘　　要：为了在加工中预测表面粗糙度,在保证铣削的同时提高生产率,将人工神经网络技术引入到铣削加工领域,利用BP神经网络,寻找切削参数和工件表面粗糙度之间的规律,建立起铣削加工表面粗糙度的预测模型。实验和仿真的结果表明,该方法能够得到较好的预测精度。To predict the surface roughness in milling, it can ensure the quantity and produetity. Artificial neural network was introduced to predict the surface roughness in milling. Making use of BP artificial neural network, the relation between the parameters of milling and surface roughness was studied, the prediction model of surface roughness was established. The result of simulation and experiment shows that this method can get a higher accuracy of prediction.

关 键 词：BP神经网络 铣削 表面粗糙度 预测 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程]