无纺布刺针缺陷检测与更换设备的设计

Design of Non-Woven Needle Defect Detection and Replacement Equipment

文章针对无纺布制造中人工依赖的刺针缺陷问题提出了基于YOLOv5算法的实时检测及更换设备。硬件系统包括图像采集、处理、退针和装针模块,通过深度学习提高了检测效率和准确性,同时满足了稳定性、实时性、可拓展性等需求。软件界面设计通过数据可视化管理和分析检测数据。总体而言,智能设备通过引入先进技术,在提高无纺布产业效率的同时,降低了成本,为可持续发展带来助力。

This article addresses the issue of manual dependence in detecting needle defects in conventional non-woven fabric manufacturing.To tackle this problem,a real-time needle defect detection and replacement system based on the YOLOV5 algorithm is proposed.The hardware system comprises modules for image capture,processing,needle retraction,and needle replacement,utilizing deep learning to enhance detection efficiency and accuracy while meeting stability,real-time,and scalability requirements.The software interface design incorporates data visualization for effective management and analysis of detection data.Overall,the proposed intelligent device introduces advanced technology,boosting efficiency,reducing costs,and creating comprehensive value for the sustainable development of the non-woven fabric industry.