Design and motion mechanism analysis of screw-driven in-pipe inspection robot based on novel adapting mechanism

IF 1.9 4区 计算机科学 Q3 ROBOTICS
Robotica Pub Date : 2024-03-04 DOI:10.1017/s0263574724000316
Jihua Yin, Xuemei Liu, Youqiang Wang, Yucheng Wang
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Abstract

In the pipeline industry, it is often necessary to monitor cracks and damage in pipelines, or need to clean the inside of the pipeline regularly, or collect adhesive on the inner wall of the pipe, but the pipe is too narrow and difficult for humans to enter, it is necessary to use a pipe machine to complete the work. In this paper, a newly designed screw-driven in-pipe inspection robot (IPIR) is proposed. Compared with common robots, this robot innovatively designs adapting mechanism. The robot can not only adapt to the change of the inner diameter size of the pipeline by using the bionic principle and the deformation characteristics of flexible components but also can pass smoothly in the horizontal/oblique/vertical pipelines and has a certain ability to cross obstacles. In addition, it can transmit images of the inner wall of the pipeline wirelessly for data analysis. Finally, through theoretical analysis and prototype construction, the performance of the robot is verified. The results show that the prototype robot can not only smoothly pass through the acrylic pipe with inner diameter of 120–138 mm but also pass through boss with a height of 3 mm.
基于新型自适应机构的螺杆驱动管道内检测机器人的设计与运动机构分析
在管道行业中,经常需要监测管道的裂缝和损坏情况,或需要定期清洁管道内部,或收集管道内壁上的粘合剂,但管道过于狭窄,人类难以进入,这就需要使用管道机械来完成工作。本文提出了一种全新设计的螺杆驱动管道内检测机器人(IPIR)。与普通机器人相比,该机器人创新性地设计了自适应机构。利用仿生学原理和柔性部件的变形特性,机器人不仅能适应管道内径尺寸的变化,还能在水平/倾斜/垂直管道中平稳通过,并具有一定的越障能力。此外,它还能无线传输管道内壁的图像,以便进行数据分析。最后,通过理论分析和原型构建,对机器人的性能进行了验证。结果表明,机器人原型不仅能顺利通过内径为 120-138 毫米的丙烯酸管道,还能通过高度为 3 毫米的凸台。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Robotica
Robotica 工程技术-机器人学
CiteScore
4.50
自引率
22.20%
发文量
181
审稿时长
9.9 months
期刊介绍: Robotica is a forum for the multidisciplinary subject of robotics and encourages developments, applications and research in this important field of automation and robotics with regard to industry, health, education and economic and social aspects of relevance. Coverage includes activities in hostile environments, applications in the service and manufacturing industries, biological robotics, dynamics and kinematics involved in robot design and uses, on-line robots, robot task planning, rehabilitation robotics, sensory perception, software in the widest sense, particularly in respect of programming languages and links with CAD/CAM systems, telerobotics and various other areas. In addition, interest is focused on various Artificial Intelligence topics of theoretical and practical interest.
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