Tool wear estimation for different workpiece materials using the same monitoring system

被引:19
|
作者
Salgado, D. R. [1 ]
Cambero, I. [1 ]
Herrera Olivenza, J. M. [1 ]
Garcia Sanz-Calcedo, J. [1 ]
Nunez Lopez, P. J. [2 ]
Garcia Plaza, E. [2 ]
机构
[1] Univ Extremadura, Dept Mech Energet & Mat Engn, Avda Elvas S-N, Badajoz 06006, Spain
[2] Univ Castilla La Mancha, Higher Tech Sch Ind Engn, E-13071 Ciudad Real, Spain
关键词
Tool wear; Flank wear; monitoring system; steel alloy; aluminium alloy; ARTIFICIAL NEURAL-NETWORK; SIGNALS;
D O I
10.1016/j.proeng.2013.08.246
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
This paper presents a tool wear monitoring system that uses the same signals and prediction strategy for monitoring the machining process of different materials, i.e., a steel and an aluminium alloy. It is an important requirement for a monitoring system to he applied in real applications. Experiments have been performed on a lathe over a range of different cutting conditions, and TiN coated tools were used. The monitoring signals used are the AC feed drive motor current and the cutting vibrations. The geometry tool parameters used as inputs are the tool angle and the radius. The performance of the proposed system was validated against different experiments. In particular, different tests were performed using different numbers of experiments obtaining a rmse for tool wear estimation of 17.63 um and 13.45 um for steel and aluminium alloys respectively.
引用
收藏
页码:608 / 615
页数:8
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