基于贝叶斯网络的平面磨削状态智能监测技术研究  

Research on Intelligent Monitoring Technique of Machining State for Surface Grinder Based on Bayesian Network

作　　者：林峰[1] 焦慧锋[2] 傅建中[2] 

机构地区：[1]衢州学院,衢州324000 [2]浙江大学浙江省先进制造技术重点实验室,杭州310027

出　　处：《中国机械工程》2011年第11期1269-1273,共5页China Mechanical Engineering

基　　金：国家科技重大专项(2009ZX04001-131)

摘　　要：为解决平面磨削过程中工件表面粗糙度预测和砂轮钝化监测困难的问题,利用贝叶斯网络建立了平面磨削状态智能监测模型。该模型在获取系统磨削用量和工件材料的基础上,在线提取磨削声发射信号的峭度系数,可以有效预测工件粗糙度和识别砂轮钝化状态,为数控系统调节加工参数提供参考。该模型在平面磨床的磨削监测试验中取得了良好的效果。In order to solve the problem of predicting workpiece quality and identifying blunt level of wheel in surface grinding,a Bayesian network model for monitoring grinding states of surface grinder was set up.The model can realize predict workpiece quality and identify blunt level of wheel by detecting kurtosis of acoustic emission with known grinding parameters and workpiece material.The results provide reference for NC system to optimize parameters.The technique obtains good effect by experiments on CNC surface grinder.

关 键 词：平面磨削 贝叶斯网络 声发射技术 粗糙度预测 

分 类 号：TG582[金属学及工艺—金属切削加工及机床]