棉纺织技术2024，Vol.52Issue(6)：55-62,8.
基于改进像素差分神经网络的碳管多层编织成形视觉检测
Visual detection of carbon tube multilayer braiding process based on improved pixel difference neural network
摘要
Abstract
Aiming at the problem that it was difficult to find the defects of the braided mesh in time in the process of braided carbon tube prefabrication.The visual detection method of carbon tube multilayer braiding process was proposed.Based on the original pixel difference neural network,SimAM module was used to realize the lightweight of the network and better attention effect,the balanced cross-entropy loss was used to solve the problem of uneven distribution of carbon tube braided mesh data,and a pixel-by-pixel braided mesh outline comparison method was proposed to judge the braiding net state.The experimental results showed that compared with the original pixel difference neural network,the improved pixel difference neural network improved the ODS and OIS by 2.4 percentage points and 2.6 percentage points respectively.It is considered that the improved pixel difference neural network can extract the outline of the braided mesh more accurately,which is more suitable for the visual detection task of the braided mesh.The method of pixel-by-pixel comparison can accurately and timely judge the outline defects of braided mesh.关键词
三维编织/像素差分神经网络/注意力机制/机器视觉/编织网轮廓/边缘检测Key words
3D braiding/pixel difference neural network/attention mechanism/machine vision/braided mesh outline/edge detection分类
计算机与自动化引用本文复制引用
王仲伟,张玉井,盛佳俊,陈玉洁,孟婥,孙以泽..基于改进像素差分神经网络的碳管多层编织成形视觉检测[J].棉纺织技术,2024,52(6):55-62,8.基金项目
国家重点研发计划(2022YFB4700603) （2022YFB4700603）
国家自然科学基金项目(51905088) （51905088）
