复合材料科学与工程Issue(5)：132-141,10.DOI:10.19936/j.cnki.2096-8000.20250528.017
基于改进YOLOv5s的拉挤板缺陷检测
Defect detection of pultrusion plate based on improved YOLOv5s
徐东亮 1赖九衡 1杨会兰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
In order to solve the problems of low detection precision and slow detection speed in traditional pul-trusion plate defect detection methods,a defect data set of glass fiber pultrusion plate was created,and a defect de-tection model of glass fiber pultrusion plate based on improved YOLOv5s was proposed.The main improvements were as follows:in the feature extraction network part,EvcBlock module was added to enhance the feature extraction a-bility of small targets,and CBAM attention mechanism was added to improve the attention of important features;the lightweight model was realized by using C3-FASTER module to optimize the C3 module;a new type of loss function ShapeIoU with shape loss was introduced into the detection end,which optimized the fitting effect of the predicted frame and the real frame,and improved the precision of defect detection.The experimental results demonstrate that:in comparison to the original YOLOv5s model,the mAP@0.5 of the improved YOLOv5s model has increased by 3.6%,reaching 88.7%,while the number of parameters has been reduced by 2.1%.The detection speed of the improved model is 121.95 frames per second,and its overall performance is superior to 5 models such as YOLOv8s,which can meet the needs of pultrusion plate defect detection.关键词
拉挤板/YOLOv5s/缺陷检测/EvcBlock/C3-faster/ShapeIoU/复合材料Key words
pultrusion plate/YOLOv5s/defect detection/EvcBlock/C3-faster/ShapeIoU/composites引用本文复制引用
徐东亮,赖九衡,杨会兰..基于改进YOLOv5s的拉挤板缺陷检测[J].复合材料科学与工程,2025,(5):132-141,10.
