首页 | 本学科首页   官方微博 | 高级检索  
     

用于监测刀具磨损的声发射(AE)特征优选方法
引用本文:陈爱弟 王信义. 用于监测刀具磨损的声发射(AE)特征优选方法[J]. 北京理工大学学报, 2000, 20(3): 270-275
作者姓名:陈爱弟 王信义
作者单位:北京理工大学机械工程与自动化学院!北京100081
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的优选特征,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了优选。

关 键 词:声发射 模糊聚类 刀具磨损 特征优选 监测

A Method of Optimizing Acoustic Emission Features in Monitoring Tool Flank Wear
CHEN Ai di,WANG Xin yi,WANG Zhong min,YANG Da yong,JIA Yu ping. A Method of Optimizing Acoustic Emission Features in Monitoring Tool Flank Wear[J]. Journal of Beijing Institute of Technology(Natural Science Edition), 2000, 20(3): 270-275
Authors:CHEN Ai di  WANG Xin yi  WANG Zhong min  YANG Da yong  JIA Yu ping
Abstract: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.
Keywords:acoustic emission  fuzzy classification  tool wear  feature optimization  
本文献已被 CNKI 维普 万方数据 等数据库收录!
点击此处可从《北京理工大学学报》浏览原始摘要信息
点击此处可从《北京理工大学学报》下载全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号