A Study on the Detection of Hole in Automotive CV Joint Boot Using Image Processing and AI Techniques; 영상처리와 인공지능 기법을 이용한 자동차 CV 조인트 부트 결함 탐지법 연구

A Study on the Detection of Hole in Automotive CV Joint Boot Using Image Processing and AI Techniques
Citations

SCOPUS

0

초록

Detecting and analyzing defects in components or systems is crucial for maintaining high-quality standards in modern manufacturing and quality control. Recently, imaging-based defect detection methods have gained popularity across various engineering fields, highlighting their growing importance. Additionally, the integration of Artificial Intelligence (AI) to improve accuracy and efficiency is rapidly advancing. This paper presents a system that uses imaging to detect holes in CV joint boots, as these holes significantly affect the overall performance and durability of the system. Moreover, it introduces a method for enhancing detection performance by applying AI techniques. Validation tests on actual CV joint boots confirmed that the proposed method improves detection performance.

키워드

CV joint boot; Hole detection; Image processing; Image sum; U-Net; YOLO
제목
A Study on the Detection of Hole in Automotive CV Joint Boot Using Image Processing and AI Techniques; 영상처리와 인공지능 기법을 이용한 자동차 CV 조인트 부트 결함 탐지법 연구
제목 (타언어)
A Study on the Detection of Hole in Automotive CV Joint Boot Using Image Processing and AI Techniques
저자
Lim, Yun-hyeok; Lee, Hyeongill
DOI
10.7736/JKSPE.025.050
발행일
2025-10
유형
Article
저널명
한국정밀공학회지
권
42
호
10
페이지
861 ~ 869