دورية أكاديمية
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Internal thread defect detection system based on multi-vision.

التفاصيل البيبلوغرافية
العنوان: Internal thread defect detection system based on multi-vision.
المؤلفون: Xiaohan Dou, Chengqi Xue, Gengpei Zhang, Zhihao Jiang
المصدر: PLoS ONE, Vol 19, Iss 5, p e0304224 (2024)
بيانات النشر: Public Library of Science (PLoS), 2024.
سنة النشر: 2024
المجموعة: LCC:Medicine
LCC:Science
مصطلحات موضوعية: Medicine, Science
الوصف: In the realm of industrial inspection, the precise assessment of internal thread quality is crucial for ensuring mechanical integrity and safety. However, challenges such as limited internal space, inadequate lighting, and complex geometry significantly hinder high-precision inspection. In this study, we propose an innovative automated internal thread detection scheme based on machine vision, aimed at addressing the time-consuming and inefficient issues of traditional manual inspection methods. Compared with other existing technologies, this research significantly improves the speed of internal thread image acquisition through the optimization of lighting and image capturing devices. To effectively tackle the challenge of image stitching for complex thread textures, an internal thread image stitching technique based on a cylindrical model is proposed, generating a full-view thread image. The use of the YOLOv8 model for precise defect localization in threads enhances the accuracy and efficiency of detection. This system provides an efficient and intuitive artificial intelligence solution for detecting surface defects on geometric bodies in confined spaces.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 1932-6203
Relation: https://doaj.org/toc/1932-6203
DOI: 10.1371/journal.pone.0304224
URL الوصول: https://doaj.org/article/816f2630a622494abd19ade377af6f8b
رقم الأكسشن: edsdoj.816f2630a622494abd19ade377af6f8b
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:19326203
DOI:10.1371/journal.pone.0304224