摘要
针对安全鞋生产中二维排样所面临的鞋片形状复杂、排样效率低、材料利用率不足等挑战,本文提出了一种基于改进临界多边形的智能排样算法。首先,引入基于切线向量的圆弧接触判定策略,有效解决带有弧边鞋片的重叠检测问题。然后,提出不完整临界多边形算法来生成可排区域,减少排样耗时。最后,构建基于形状特征的排样策略,以提高材料利用率。实验结果表明,本文提出的排样算法的最大材料利用率为91.27%,平均材料利用率为79.10%,较人工排样提升8.36%。单个鞋片的排样用时在1.21~1.63 s之间,较人工排样缩短了68.2%。该算法有效解决了形状复杂且不规则的安全鞋鞋片的在线排样问题。
To address the challenges of complex vamp component shapes,low nesting efficiency,and insufficient material utilization in the two-dimensional nesting for safety shoe production,this paper proposes an intelligent nesting algorithm based on an improved No-fit polygon algorithm.First,a tangential vector-based arc contact detection strategy is introduced to effectively solve the overlap detection problem of vamp components with arcs.Then,an incomplete no-fit polygon algorithm is employed to generate the feasible nesting area,reducing nesting time.Finally,a vamp component shape feature-based nesting strategy is developed to enhance material utilization.Experimental results show that the proposed nesting algorithm achieves a maximum material utilization rate of 91.27%and an average material utilization rate of 79.10%,representing an 8.36%improvement over manual nesting.The nesting time for a vamp component ranges from 1.21 to 1.63 s,reducing time by 68.2%compared to manual nesting.The proposed algorithm effectively solves the online nesting problem for complex and irregularly shaped vamp components.
作者
陈炜杰
陈炜
马莹
卢木旺
林鸿杰
Chen Weijie;Chen Wei;Ma Ying;Lu Muwang;Lin Hongjie(School of Electronic,Electrical Engineering and Physics,Fujian University of Technology,Fuzhou 350118,China;Fujian Provincial Technology Development Base for Industrial Integration Automation,Fuzhou 350118,China;Fujian AoXiang Security Technology Co.,Ltd.,Nanping 353099,China)
出处
《电子测量技术》
北大核心
2025年第14期106-117,共12页
Electronic Measurement Technology
基金
福建省科技计划项目(创新基金项目)(2024C0045)资助。
关键词
安全鞋
鞋片排样
不规则形状
临界多边形算法
重叠检测
safety shoe
vamp component nesting
irregular shape
no-fit polygon
overlap detection
作者简介
通信作者:陈炜杰,硕士研究生,主要研究方向为智能控制。E-mail:2221905011@smail.fjut.edu.cn;陈炜,副教授,硕士生导师,主要研究方向为智能控制与机器视觉技术、基于PLC的自动化系统集成。E-mail:chenwei@fjut.edu.cn;马莹,副教授,硕士生导师,主要研究方向为智能控制、通信网。E-mail:may@fjut.edu.cn。
