In-Process Tool Wear Measurement System Based on Image Analysis for CNC Drilling Machines

被引：48
作者：
Lins, Romulo Goncalves [1 ]
Guerreiro, Bruno [2 ]
Marques de Araujo, Paulo Ricardo [3 ]
Schmitt, Robert [4 ]
机构：
[1] Fed Univ ABC, Ctr Engn Modeling & Appl Social Sci, BR-09250580 Santo Andre, SP, Brazil
[2] Fraunhofer Inst Prod Technol IPT, D-52074 Aachen, Germany
[3] Fed Univ ABC, Grad Program Engn & Innovat Management, BR-09250580 Santo Andre, SP, Brazil
[4] Rhein Westfal TH Aachen, Lab Machine Tools & Prod Engn WZL, D-52062 Aachen, Germany
来源：
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT | 2020年 / 69卷 / 08期
关键词：
Tools; Cutting tools; Monitoring; Machining; Sensors; Cameras; Image processing; Automation; computer vision system; image analysis; machining process; rotating cutting tool wear measurement;
D O I：
10.1109/TIM.2019.2961572
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
Tool condition monitoring (TCM) has been a constant field of research. Conventionally, some sensors are installed at specific parts of the machine, and by using the signal-processing techniques, the tool wear is estimated. In this article, a direct system based on image analysis has been developed to automate the in-process tool wear measurement. The method uses only a single camera installed inside the machine and a tree-stage measurement process composed of image treatment, image comparison, and wear measurement. Experimental results show that the detection of similar images has a success index rate (SIR) equal to 98.89%, whereas the measurement error of the average flank wear and the maximum flank wear is estimated to be 3.57% and 2.92%, respectively.
引用
收藏
页码：5579 / 5588
页数：10
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