用于监测刀具磨损的声发射(AE)特征优选方法  

A Method of Optimizing Acoustic Emission Features in Monitoring Tool Flank Wear

作　　者：陈爱弟[1] 王信义[1] 王忠民[1] 杨大勇[1] 贾玉平[1] 

机构地区：[1]北京理工大学机械工程与自动化学院,北京100081

出　　处：《北京理工大学学报》2000年第3期270-275,共6页Transactions of Beijing Institute of Technology

摘　　要：研究合理选择声发射信号特征以实现实时监测刀具磨损量 .利用模糊聚类特征优选方法对声发射传感器特征信息进行优选 ,并在此基础上给出了模糊聚类优选声发射特征的一般结论 .给出了声发射信号的模糊聚类优选方法和优选特征 ,并在实时检测刀具磨损量的实验中得到验证 .实验表明 ,利用模糊聚类特征优选方法能有效地对刀具磨损监测中的声发射特征进行优选 .The sensitive features of AE were properly chosen to monitor tool flank wear. Based on fuzzy classification the features of AE signal were optimized, and on this basis a general conclusion of optimizing AE characteristics was reached. The method of using fuzzy classification to optimize the AE signal feature and the optimum features were presented and proved in the experiment of real time detecting tool wear. The experiments showed that using fuzzy classification can effectively optimize AE features.

关 键 词：声发射 模糊聚类 刀具磨损 特征优选 监测 

分 类 号：TG506[金属学及工艺—金属切削加工及机床]