Detailed Information

Cited 0 time in webofscience Cited 0 time in scopus
Metadata Downloads

머신비전 시스템을 이용한 마이크로드릴 마멸의 상태감시Monitoring of Micro-Drill Wear by Using the Machine Vision System

Other Titles
Monitoring of Micro-Drill Wear by Using the Machine Vision System
Authors
정성종최영조
Issue Date
Jun-2006
Publisher
대한기계학회
Keywords
Edge Detection; 윤곽선 검출; Machine Vision; 머신비전; Micro-Drill; 마이크로-드릴; Reliability Estimation; 신뢰도 평가; Shape from Focus; 초점결상; Wear; 마멸
Citation
대한기계학회논문집 A, v.30, no.6, pp.713 - 721
Indexed
KCI
Journal Title
대한기계학회논문집 A
Volume
30
Number
6
Start Page
713
End Page
721
URI
https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/181315
ISSN
1226-4873
Abstract
Micro-drill wear deteriorates accuracy and productivity of the micro components. In order to improve productivity and quality of micro components, it is required to investigate micro-drill wear exactly. In this study, a machine vision system is proposed to measure the wear of micro-drills using a precision servo stage. Calibration experiments are conducted to compensate for the machine vision system. In this paper, worn volume, area and length are defined as wear amounts. Micro-drill wear is reconstructed as the 3D topography and the quantized wear amount by using the shape from focus (SFF) method and wear parameters. Experiments have been conducted with HSS twist micro-drills and SM45C carbon steel workpieces. Validity of the proposed machine vision system is confirmed through experiments.
Files in This Item
Go to Link
Appears in
Collections
서울 공과대학 > 서울 기계공학부 > 1. Journal Articles

qrcode

Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.

Related Researcher

Researcher Chung, Sung Chong photo

Chung, Sung Chong
서울 공과대학 (서울 기계공학부)
Read more

Altmetrics

Total Views & Downloads

BROWSE