纺织学报 ›› 2023, Vol. 44 ›› Issue (08): 197-204.doi: 10.13475/j.fzxb.20220200701

• 机械与器材 • 上一篇    下一篇

智能服装缝制关键技术及成套装备研发

陈罡1(), 金贵阳2, 吴菁1, 罗千3   

  1. 1.浙江机电职业技术学院 自动化学院, 浙江 杭州 310059
    2.宁波大学 机械工程与力学学院, 浙江 宁波 315210
    3.舒普智能技术股份有限公司, 浙江 宁波 315100
  • 收稿日期:2022-02-09 修回日期:2023-04-11 出版日期:2023-08-15 发布日期:2023-09-21
  • 作者简介:陈 罡(1974—),男,教授,博士。主要研究方向为缝制装备自动化智能化。E-mail:bastarcg@163.com
  • 基金资助:
    宁波市2025科技重大项目(2020Z072);浙江省博士后择优资助项目(ZJ2021086)

Research and development of key technologies and whole-set equipment for intelligent sewing

CHEN Gang1(), JIN Guiyang2, WU Jing1, LUO Qian3   

  1. 1. School of Automation, Zhejiang Institute of Mechanical & Electrical Engineering, Hangzhou, Zhejiang 310059, China
    2. Faculty of Mechanical Engineering & Mechanics, Ningbo University, Ningbo, Zhejiang 315210, China
    3. Supreme Intelligent Technology Co., Ltd., Ningbo, Zhejiang 315100, China
  • Received:2022-02-09 Revised:2023-04-11 Published:2023-08-15 Online:2023-09-21

摘要:

针对面料缝合过程中人力需求高、自动化程度低、效率低等问题,结合机器视觉、工业机械臂和缝机等,设计并研发了从上料到缝合到下料的智能缝制成套装备。首先,对基于拉线编码器的机械臂绝对定位误差优化补偿技术、基于Canny算子的面料轮廓识别与关键点提取技术、基于比例积分微分(PID)闭环控制算法的机械臂与缝纫机速度的同步控制技术进行了研究。然后,针对具体的应用需求研发了双层面料智能缝制设备,并对其进行了简单介绍。案例分析结果表明,通过几种技术的结合,提高了缝制成套装备机械臂的绝对定位精度、面料轮廓识别提取能力、缝制质量的一致性,减少了人工需求,助力服装缝制行业的转型升级。

关键词: 机器视觉, 误差补偿, 轮廓提取, 同步控制, 智能缝制, 服装

Abstract:

Objective In response to problems such as high labor demand, low automation, and low efficiency in the process of fabric stitching, machine vision, industrial robot, and sewing machine technologies were studied and applied to the design and development of intelligent sewing equipment. By combining these technologies, it helps to improve the absolute positioning accuracy of the industrial robot, as well as the ability to extract fabric contours and ensure the consistency of sewing quality. This has reduced the need for manual labor and has helped drive the transformation and upgrading of the garment sewing industry.

Method Firstly, the absolute positioning kinematics parameter error compensation technology of industrial robot based on wire encoder was studied, so that the absolute positioning accuracy of industrial robot can meet the requirements of sewing task. Secondly, the technology of fabric contour and key points extraction based on Canny operator was studied, which provides data basis for the sewing path plan. Thirdly, the speed synchronization control algorithm of industrial robot and sewing machine based on proportional integral differential (PID) law was developed to solve the problem of irregular stitches caused by the unsynchronization of industrial robot and sewing machine.

Results A double-layer garment piece intelligent sewing equipment consisting of industrial robot, camera, sewing machine, working platform, loading, unloading and other auxiliary mechanisms was developed according to customer needs (Fig. 3,4). The calibration software was developed by applying the optimization compensation technology for the absolute positioning error of the industrial robot based on the wire encoder, which reduced the absolute positioning accuracy error of the central point of the industrial robot tool from the average 1.263 5 mm to 0.128 5 mm. Sewing effect showed the comparison of sewing effects before and after optimization of absolute positioning error. Sewing effect before error compensation shows the sewing stitches prior to error optimization and sewing effect after error compensation shows the sewing stitches after error optimization. It can be seen from sewing effect that the sewing quality of the fabric was greatly improved by adopting the error optimization technology. Using fabric contour extraction technology based on Canny operator, a fabric contour and key point's extraction program based on OpenCV was developed. The original fabric image was a fabric of arbitrary shape, representing various contours of real fabric such as straight line, arc and curve. Fabric contour extraction showed the effect of the contour and key points extraction program, generating different numbers of key points according to different contour curvature. The larger the curvature, the more key points were to be extracted, which was convenient for trajectory planning of the industrial robot and improves the sewing quality. The control block diagram and corresponding control program were constructed by using the speed synchronization control technology of the industrial robot and the sewing machine. The sewing machine needle speed was on open loop control, and its speed was proportional to the Tool Center Point (TCP) speed of the industrial robot. The speed of the cloth feeding wheel of the sewing machine was controlled in a closed loop, which improved the ability of the cloth feeding wheel speed to follow the TCP speed of the industrial robot. Sewing effect and stitches demonstrated the effect before and after the speed synchronization of the industrial robot and the sewing machine, leading to significant improvement of the quality of stitches.

Conclusion Combined with machine vision, absolute positioning error compensation of industrial robot, contour extraction technology, synchronous control technology of manipulator and sewing machine, and this research systematically studied the technical system required for intelligent sewing equipment. The research and development of intelligent sewing equipment has effectively reduced the number of equipment operators, solved the problem of shortage of sewing workers, provided technical accumulation for the automation and intelligence of sewing equipment, and also provided a technical basis for the automation, intelligence and digital transformation of the sewing process in the sewing industry. It is recommended that the sewing equipment should be further improved mainly from the following two aspects, i.e., the 6-axis industrial robot should be changed to Selective Compliance Assembly Robot Arm (SCARA) to reduce equipment costs and improve the absolute positioning accuracy, and a simple and easy-to-use human-computer interface should be designed to facilitate operation and switching sewing tasks.

Key words: machine vision, error compensation, contour extraction, synchronization technology, intelligent sewing

中图分类号: 

  • TH166

图1

智能缝制成套装备组成"

图2

基坐标系下两点距离误差"

图3

缝制装备上料平台"

图4

缝制装备缝制模块"

图5

缝制装备控制系统架构"

图6

误差优化软件机械臂标定界面"

表1

机械臂的误差补偿前后的TCP误差对比"

补偿前后 最小值 均值 最大值
误差补偿前 0.590 1 1.263 5 2.568 6
误差补偿后 0.050 6 0.128 5 0.205 7

图7

误差优化前后缝制效果"

图8

面料轮廓和关键点提取"

图9

机械臂与缝纫机同步控制框图"

图10

机械臂与缝针未同步时缝制效果"

图11

曲率大处针迹不变的效果图"

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