文献类型：期刊文献

中文题名：线性机与粗糙集综合聚类的铣刀破损状态识别

英文题名：Tool Status Recognition Based on Cluster Algorithm Integrating Linear Machine and Rough Set

作者：刘岩[1];刘璨[1]

机构：[1]广东海洋大学工程学院,广东湛江524088

年份：2006

卷号：35

期号：7

起止页码：109

中文期刊名：机电工程技术

外文期刊名：Mechanical & Electrical Engineering Technology

语种：中文

中文关键词：线性机;粗糙集;刀具;状态识别

外文关键词：linear machine;rough set;tool;status recognition

中文摘要：在铣刀状态识别中,为更好地拟合训练样本数据,采用了线性机和粗糙集结合的算法,对训练样本数据进行监督学习,得到了刀具状态分类规则。样本训练的计算简单,分类规则得到简化,样本的分类正确率高。表明应用该算法可较好地获得刀具状态识别规则。

外文摘要：For milling-cutter-status recognition,in order to well fit training sample data,the algorithm of integrating linear machine and rough set is applied.Training data is supervised learned,and the classification rule is obtained.The calculation of learning is simple,classification rule is simplified,and sample classification right ratio is high.These show that tool-status-recognition rule can be well obtained with this algorithm.