摘要
为了解刀具在切削时的实际状况,课题组提出了基于切削温度的刀具状态实时监测的方案。采用仿真与试验相结合相验证的方法,对刀具在新刀、早期磨损、严重磨损以及失效4种状态下的切削温度进行分析。通过试验采集刀具磨损及失效的温度信号数据,建立了基于最小模糊度的隶属度函数优化模型,用于诊断刀具加工过程中的磨损及失效状态。应用结果表明,该方法可以实现对刀具磨损及失效状态的实时监测,对提高机床的加工效率及加工精度具有重要意义。
To understand the actual condition of tool at the time of cutting,a real-time monitoring scheme of cutting tool condition based on cutting temperature was proposed.The cutting temperature of cutting tool in four states:new cutting tool,early wear,severe wear and failure was analyzed by combining simulation with experiment.An optimization model of membership function based on minimum ambiguity was established by collecting the temperature signal data of tool wear and failure to diagnose tool wear and failure during machining.The application results show that this method can realize the real-time monitoring of tool wear and failure state,and is of great significance to improve the processing efficiency and accuracy of machine tools.
作者
丁宁
张敏良
郭东升
赵森
吴经洋
DING Ning;ZHANG Minliang;GUO Dongsheng;ZHAO Sen;WU Jingyang(School of Mechanical and Automotive Engineering,Shanghai University of Engineering Science,Shanghai 201620,China)
出处
《轻工机械》
CAS
2019年第5期34-38,共5页
Light Industry Machinery
关键词
刀具磨损
切削温度
模糊隶属度
实时监测
特征数据库
tool wear
cutting temperature
fuzzy membership
real-time monitoring
characteristics database