Design of hexapod robot equipped with omnidirectional vision sensor for defect inspection of pipeline’s inner surface

六足动物 全向天线 管道(软件) 曲面(拓扑) 机器人 计算机视觉 计算机科学 人工智能 声学 物理 数学 电信 几何学 天线(收音机) 程序设计语言
作者
Zhanshe Guo,Jing Wang,Fuqiang Zhou,P. F. Zhang,Zhipeng Song,Haishu Tan
出处
期刊:Measurement Science and Technology [IOP Publishing]
卷期号:35 (11): 115901-115901
标识
DOI:10.1088/1361-6501/ad6922
摘要

Abstract Defect detection of inner surface of precision pipes is a crucial aspect of ensuring production safety. Currently, pipeline defect detection primarily relies on recording video for manual recognition, with urgent need to improve automation, quantification and accuracy. This paper presents a hexapod in-pipe robot with carrying capacity designed to transport the omnidirectional vision sensor to specified location within unreachable pipelines. The feasibility of the robot’s mechanical design and sensor load-carrying module is analyzed using theory calculations, motion simulations and finite element method. To address the challenges of small pixel ratio and weak background changes in panoramic images, a tiny defect segmentor based on ResNet is proposed for detecting tiny defects on the inner surface of pipelines. The hardware and software systems are implemented, and the motion performance of the pipeline robot is validated through experiments. The results demonstrate that the robot achieves stable movement at a speed of over 0.1 m s −1 and can adapt to pipe diameter ranging from of 110 to 130 mm. The novelty of the robot lies in providing stable control of the loaded vision sensor, with control precision of the rotation angle and the displacement recorded at 1.84% and 0.87%, respectively. Furthermore, the proposed method achieves a detection accuracy of 95.67% for tiny defects with a diameter less than 3 mm and provides defect location information. This pipeline robot serves as an essential reference for development of in-pipe 3D vision inspection system.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
吃饱了嘛发布了新的文献求助10
1秒前
yqf完成签到,获得积分10
2秒前
2秒前
4秒前
张蕾完成签到,获得积分10
4秒前
梁大丹发布了新的文献求助10
6秒前
对苏发布了新的文献求助10
7秒前
科研通AI5应助心灵美的枫采纳,获得10
8秒前
Carsen完成签到,获得积分10
8秒前
ago发布了新的文献求助10
9秒前
13秒前
痴情的博超完成签到,获得积分0
14秒前
一个快乐的吃货完成签到,获得积分10
14秒前
Ava应助liang2508采纳,获得10
14秒前
科研通AI6应助wenjingchen采纳,获得10
17秒前
17秒前
17秒前
勤恳的天亦应助张延旭采纳,获得30
17秒前
量子星尘发布了新的文献求助150
18秒前
FashionBoy应助闻笙采纳,获得10
18秒前
威武冷雪发布了新的文献求助10
19秒前
Lucas应助过奖啦采纳,获得10
20秒前
CC完成签到 ,获得积分10
20秒前
20秒前
让我康康完成签到 ,获得积分10
22秒前
2jz发布了新的文献求助10
23秒前
天天快乐应助咚咚咚采纳,获得10
23秒前
充电宝应助悦耳的妙芹采纳,获得10
23秒前
Leedesweet完成签到 ,获得积分10
24秒前
549发布了新的文献求助10
24秒前
An发布了新的文献求助10
26秒前
威武冷雪完成签到,获得积分10
26秒前
27秒前
27秒前
27秒前
花花完成签到,获得积分10
30秒前
旧辞完成签到,获得积分10
31秒前
31秒前
pHsycho完成签到,获得积分10
31秒前
量子星尘发布了新的文献求助150
32秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Zeolites: From Fundamentals to Emerging Applications 1500
Encyclopedia of Materials: Plastics and Polymers 1000
Architectural Corrosion and Critical Infrastructure 1000
Early Devonian echinoderms from Victoria (Rhombifera, Blastoidea and Ophiocistioidea) 1000
Hidden Generalizations Phonological Opacity in Optimality Theory 1000
Handbook of Social and Emotional Learning, Second Edition 900
热门求助领域 (近24小时)
化学 医学 生物 材料科学 工程类 有机化学 内科学 生物化学 物理 计算机科学 纳米技术 遗传学 基因 复合材料 化学工程 物理化学 病理 催化作用 免疫学 量子力学
热门帖子
关注 科研通微信公众号,转发送积分 4922714
求助须知:如何正确求助?哪些是违规求助? 4193375
关于积分的说明 13024710
捐赠科研通 3965192
什么是DOI,文献DOI怎么找? 2173183
邀请新用户注册赠送积分活动 1190843
关于科研通互助平台的介绍 1100208