轮槽半精铣刀寿命自适应预测方法研究  

Adaptive Life Prediction Method of Wheel Groove Semi Finishing Cutter

作　　者：闫杉[1] 胡小锋[1] 刘颖超[1] 张洁[1] YAN Shan HU Xiao-feng LIU Ying-chao ZHANG Jie(CIMS Institute, School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai 200240, Chin)

机构地区：[1]上海交通大学机械与动力工程学院计算机集成制造研究所,上海200240

出　　处：《组合机床与自动化加工技术》2016年第9期95-98,共4页Modular Machine Tool & Automatic Manufacturing Technique

基　　金：国家自然科学基金重点项目(51435009);上海市科委高新技术领域项目资助(14111104801)

摘　　要：为预测汽轮机转子枞树型轮槽半精铣刀寿命,提出了一种基于非线性回归模型的刀具寿命自适应在线预测方法,即通过提取与刀具磨损相关的功率信号特征和声发射信号特征,利用Kmeans聚类分析对半精铣削过程进行分类,针对不同类别的加工过程分别建立刀具寿命非线性预测模型,实现自适应的刀具状态在线预测及刀具寿命的估算。实验结果表明此方法可以准确预测出刀具的失效时间,为刀具的合理更换提供依据。The online life adaptive prediction method is proposed to predict turbine rotor groove wheel fir tree semi finishing milling cutter＇s life,which is based on nonlinear regression model. The features of pow-er signal and acoustic emission signal features are extracted,which is associated with tool wear,then semi finishing milling process are classified using K-means clustering analysis. For different processes,nonlinear tool life prediction models are established individually to achieve the on-line adaptive tool condition prediction and tool life calculation. Experimental results showthat this method can accurately predict the tool failure time,which provides a basis for the reasonable replacement of the tool.

关 键 词：非线性回归模型 刀具寿命 聚类分析 自适应在线预测 

分 类 号：TH17[机械工程—机械制造及自动化] TG506[金属学及工艺—金属切削加工及机床]