Visual inspection intelligent robot technology for large infusion industry

IF 1.1 Q3 COMPUTER SCIENCE, THEORY & METHODS Open Computer Science Pub Date : 2023-01-01 DOI:10.1515/comp-2022-0262
Qilang Liang, Bangshun Luo
{"title":"Visual inspection intelligent robot technology for large infusion industry","authors":"Qilang Liang, Bangshun Luo","doi":"10.1515/comp-2022-0262","DOIUrl":null,"url":null,"abstract":"Abstract The application of intelligent technology has realized the transformation of people’s production and lifestyle, and it has also promoted the development of the field of medicine. At present, the intensity of intelligence in the field of medicine is increasing. By using its cash methods and techniques combined with the mechanical field, this article proposes to use visual inspection technology to understand the fusion of the medical field and the mechanical field. It is helpful to analyze and solve objective problems such as low efficiency in current infusion and insufficient rigidity of large infusion plastic bottles. Drawing on the principles and laws of deep learning algorithms and neural networks, the technical research of intelligent robots for visual inspection is carried out to realize the intelligence of infusion robots. In the research accuracy of detection, the detection rate of standard particles higher than 85 µM has reached almost 100%, and the rate of 50 µM standard particles is lower and unstable. The detection effect of the control light bulb control was different, and the detection rate was between 50 and 80%, which was obviously worse than the detection robot effect. Therefore, the current research on the technology of intelligent robots is very important.","PeriodicalId":43014,"journal":{"name":"Open Computer Science","volume":" ","pages":""},"PeriodicalIF":1.1000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Open Computer Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1515/comp-2022-0262","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, THEORY & METHODS","Score":null,"Total":0}
引用次数: 1

Abstract

Abstract The application of intelligent technology has realized the transformation of people’s production and lifestyle, and it has also promoted the development of the field of medicine. At present, the intensity of intelligence in the field of medicine is increasing. By using its cash methods and techniques combined with the mechanical field, this article proposes to use visual inspection technology to understand the fusion of the medical field and the mechanical field. It is helpful to analyze and solve objective problems such as low efficiency in current infusion and insufficient rigidity of large infusion plastic bottles. Drawing on the principles and laws of deep learning algorithms and neural networks, the technical research of intelligent robots for visual inspection is carried out to realize the intelligence of infusion robots. In the research accuracy of detection, the detection rate of standard particles higher than 85 µM has reached almost 100%, and the rate of 50 µM standard particles is lower and unstable. The detection effect of the control light bulb control was different, and the detection rate was between 50 and 80%, which was obviously worse than the detection robot effect. Therefore, the current research on the technology of intelligent robots is very important.
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
面向大型输液行业的视觉检测智能机器人技术
摘要智能技术的应用实现了人们生产生活方式的转变,也促进了医学领域的发展。目前,医学领域的智力强度正在提高。本文将其现金支付方法和技术与机械领域相结合,提出利用视觉检测技术来理解医学领域与机械领域的融合。有助于分析和解决目前输液效率低、大型输液塑料瓶刚性不足等客观问题。借鉴深度学习算法和神经网络的原理和规律,对用于视觉检测的智能机器人进行技术研究,以实现输液机器人的智能化。在研究检测精度时,标准颗粒物的检测率高于85 µM几乎达到100% µM标准颗粒较低且不稳定。控制灯泡控制的检测效果不同,检测率在50-80%之间,明显比检测机器人的效果差。因此,当前对智能机器人技术的研究具有十分重要的意义。
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
Open Computer Science
Open Computer Science COMPUTER SCIENCE, THEORY & METHODS-
CiteScore
4.00
自引率
0.00%
发文量
24
审稿时长
25 weeks
期刊最新文献
Artificial intelligence-based public safety data resource management in smart cities Application of fingerprint image fuzzy edge recognition algorithm in criminal technology Application of SSD network algorithm in panoramic video image vehicle detection system Data preprocessing impact on machine learning algorithm performance RFID supply chain data deconstruction method based on artificial intelligence technology
×
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