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
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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.
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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。
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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
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