复合材料科学与工程Issue(2)：145-150,6.DOI:10.19936/j.cnki.2096-8000.20250228.018
基于机器视觉玻璃纤维束缺陷检测技术的研究
Research on defect detection technology of glass fiber bundle based on machine vision
徐东亮 1薛紫阳 1赖九衡1
作者信息
- 1. 武汉理工大学 机电工程学院,武汉 430070
- 折叠
摘要
Abstract
Glass fiber bundle is a whole composed of hundreds of small glass fibers.Because of this structure,it is difficult to identify yarn-breaking defects in the production process of filament winding products.In order to solve this problem,a method based on machine vision is proposed to detect the defects of glass fiber bundles and the loca-tion of defects.The real-time image of the glass fiber bundle on the yarn road is captured by the industrial camera,and the image is transmitted to the computer.The image of each frame of the glass fiber bundle is processed by the OpenCV library,and the outline and defect characteristics of each glass fiber bundle are obtained.According to the defect characteristics,whether the glass fiber bundle is completely or partially broken is judged by the defect detec-tion algorithm,and the location of the defect is determined by using the KNN algorithm.The movement rate of glass fiber bundle is 1 m/s,and 600 images are collected at a frame rate of 30 fps for experimental verification.The de-tection data show that the comprehensive accuracy is up to 96.6%,which meets the requirements of glass fiber bun-dle defect detection.关键词
机器视觉/玻璃纤维束/图像处理/缺陷检测/KNN分类算法/复合材料Key words
machine vision/glass fiber bundle/image processing/defect detection/KNN classification algo-rithm/composites引用本文复制引用
徐东亮,薛紫阳,赖九衡..基于机器视觉玻璃纤维束缺陷检测技术的研究[J].复合材料科学与工程,2025,(2):145-150,6.
