دورية أكاديمية
Internal thread defect detection system based on multi-vision.
العنوان: | Internal thread defect detection system based on multi-vision. |
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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 |
تدمد: | 19326203 |
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DOI: | 10.1371/journal.pone.0304224 |