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

被引：51

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

页码：5579 / 5588

页数：10

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