A data-driven approach for tool wear recognition and quantitative prediction based on radar map feature fusion

X Li,X Liu, C Yue, S Liu, B Zhang,R Li,SY Liang,L Wang

Measurement（2021）

引用 24|浏览9

暂无评分

摘要

•A data-driven tool wear recognition and prediction approach is proposed.•A radar map feature fusion method is proposed to obtain tool health indicator.•The Adaboost-DT is developed for tool wear state recognition.•The SBiLSTM enables quantitative prediction of tool wear with limited data input.

查看译文

关键词

Tool wear monitoring,Radar map feature fusion,Tool health indicator,Adaboost-DT,SBiLSTM

AI 理解论文

溯源树

样例

生成溯源树，研究论文发展脉络

Chat Paper

正在生成论文摘要