마이크로 드릴비트 연마 시스템 연삭휠의 마모 진단 연구A Study on the Wear Condition Diagnosis of Grinding Wheel in Micro Drill-bit Grinding System
- Other Titles
- A Study on the Wear Condition Diagnosis of Grinding Wheel in Micro Drill-bit Grinding System
- Authors
- 김민섭; 허장욱
- Issue Date
- Mar-2022
- Publisher
- 한국기계가공학회
- Keywords
- Micro Drillbit Grinding System(드릴비트 연마 시스템); Machine Learning(머신러닝); Grinding Wheel(연삭휠); Wear Diagnostics(마모 진단)
- Citation
- 한국기계가공학회지, v.21, no.3, pp.77 - 85
- Journal Title
- 한국기계가공학회지
- Volume
- 21
- Number
- 3
- Start Page
- 77
- End Page
- 85
- URI
- https://scholarworks.bwise.kr/kumoh/handle/2020.sw.kumoh/21054
- DOI
- 10.14775/ksmpe.2022.21.03.077
- ISSN
- 1598-6721
- Abstract
- In this study, to diagnose the grinding state of a micro drill bit, a sensor attachment location was selectedthrough random vibration analysis of the grinding unit of the micro drill-bit grinding system. In addition, thevibration data generated during the drill bit grinding were collected from the grinding unit for the grindingwheels under the steady and worn conditions, and data feature extraction and dimension reduction wereperformed. The wear of the micro-drill-bit grinding wheel was diagnosed by applying KNN, a machine-learningalgorithm. The classification model showed excellent performance, with an accuracy of 99.2%. The precision,recall and f1-score were higher than 99% in both the steady and wear conditions.
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Collections - School of Mechanical System Engineering > 1. Journal Articles
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