Automatic Assembly System of Shore Connection Cable based on Machine Vision

Liguo Shi, Zhigen Xu, Yanzhen Li, Yang Hu
{"title":"Automatic Assembly System of Shore Connection Cable based on Machine Vision","authors":"Liguo Shi, Zhigen Xu, Yanzhen Li, Yang Hu","doi":"10.1109/INSAI54028.2021.00018","DOIUrl":null,"url":null,"abstract":"At present, the shore power connection in China is mainly completed by manual towing operation, which requires the mutual cooperation of wharf operators and mooring personnel. The operation has a large amount of labor, low efficiency, and poor working environment. With the development of science and technology and the improvement of industrial automation level, machine vision technology has been widely used in various fields. It is possible to use machine vision technology to replace manual connection of shore power cables. Therefore, in order to further improve the intelligent level of the port shore power system, solve the problem that the reverse power transmission operation depends on the manual dragging of the cable by the crew, improve the intelligent and automation level of the shore power collection system, and ensure the control and visual management of the ship shore power collection, the design of the shore power line and cable automatic assembly system based on machine vision is of great significance.","PeriodicalId":232335,"journal":{"name":"2021 International Conference on Networking Systems of AI (INSAI)","volume":"127 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 International Conference on Networking Systems of AI (INSAI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/INSAI54028.2021.00018","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

At present, the shore power connection in China is mainly completed by manual towing operation, which requires the mutual cooperation of wharf operators and mooring personnel. The operation has a large amount of labor, low efficiency, and poor working environment. With the development of science and technology and the improvement of industrial automation level, machine vision technology has been widely used in various fields. It is possible to use machine vision technology to replace manual connection of shore power cables. Therefore, in order to further improve the intelligent level of the port shore power system, solve the problem that the reverse power transmission operation depends on the manual dragging of the cable by the crew, improve the intelligent and automation level of the shore power collection system, and ensure the control and visual management of the ship shore power collection, the design of the shore power line and cable automatic assembly system based on machine vision is of great significance.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
基于机器视觉的岸接电缆自动装配系统
目前国内岸电连接主要以人工拖曳作业完成,需要码头作业人员和系泊人员相互配合。该操作用劳动量大,效率低,工作环境差。随着科学技术的发展和工业自动化水平的提高,机器视觉技术在各个领域得到了广泛的应用。利用机器视觉技术代替人工连接岸电电缆是可能的。因此,为了进一步提高港口岸电系统的智能化水平,解决逆向送电操作依赖船员手动拖拽电缆的问题,提高岸电采集系统的智能化和自动化水平,保证船舶岸电采集的控制和可视化管理,基于机器视觉的岸电线路电缆自动装配系统的设计具有重要意义。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
A Review of Artificial Intelligence in Preoperative Clinical Staging of Liver Cancer Head Pose Estimation of Stroke Patients Based on Depth Residual Network Cable Life Prediction Based on BP Neural Network An Improved Ant Colony Optimization Algorithm for Multi-Agent Path Planning Application of License Plate Number Recognition Based on Deep Learning Method in Intelligent Building Security System
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1