基于在线学习的数控加工刀具寿命动态预测方法  

Dynamic Prediction Method of Cutting Tool Life in NC Machining Based on Online Learning

作　　者：王强[1] 李迎光[1] 郝小忠[1] 刘长青[1] 陈海吉 WANG Qiang;LI Yingguang;HAO Xiaozhong;LIU Changqing;CHEN Haiji(College of Mechanical and Electrical Engineering,Nanjing University of Aeronautics and Astronautics,Nanjing 210016,China)

机构地区：[1]南京航空航天大学机电学院,南京210016

出　　处：《航空制造技术》2019年第7期49-53,共5页Aeronautical Manufacturing Technology

基　　金：2015年国家重大专项(2015ZX04001002)

摘　　要：预测刀具寿命对保证零件质量和控制加工成本意义重大,但刀具磨损过程复杂多变,刀具剩余寿命受工况影响难以准确预测。针对以上问题,提出了一种基于在线学习的刀具寿命动态预测方法,以长短时记忆网络为基础模型,融合在线学习模块,使得模型能够在加工过程中自动更新参数,实现变工况下刀具寿命的精确预测。进行了铣削加工试验,结果表明,刀具寿命动态预测方法可以有效提升刀具寿命预测精度。The prediction of tool life is of great significance to ensure the quality of parts and control the cost of machining. However, the tool wear process is complex and changeable, and it is difficult to accurately predict the residual life of the cutting tools affected by machining conditions. To solve the above problems, this paper presents a dynamic prediction method of tool life based on online learning. Using long-short term memory as base model and integrating the online learning module, the final model can automatically update the parameters during the machining process, and the accurate prediction of tool life under variable working conditions can be realized. The milling experiment was carried out, and the experimental results show that the dynamic prediction method of tool life can effectively improve the precision of tool life prediction.

关 键 词：在线学习 数控加工 刀具磨损 寿命预测 动态预测 

分 类 号：TG659[金属学及工艺—金属切削加工及机床] V260.6[航空宇航科学与技术—航空宇航制造工程]