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蠕动式悬索桥主缆检测机器人研制

Development of Main Cable Inspection Robot for Suspension Bridge-CCRobot-M
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摘要 针对悬索桥主缆坡度大、直径大,索夹及附属结构障碍和人工检测存在作业难度大、效率低、盲区多、安全风险高的工程难题,设计了一种可实现主缆智能化检测的蠕动式悬索桥主缆检测机器人。该机器人通过模拟生物攀爬动作,以主缆检修道扶手绳为攀爬载体,一组抱靴夹紧扶手绳,一组抱靴松开向前移动,2组抱靴交替开合,实现蠕动攀爬,并通过携带的视觉传感器阵列,对悬索桥主缆进行全覆盖检测;同时,分析研究了主缆检测机器人沿扶手绳攀爬的力学特点和运动功能,对其适应性和可靠性进行了实桥测试。结果表明,机器人可沿主缆平稳运行,顺利越过索夹,获得主缆全覆盖检测图像数据。 For the inspection of main cables of suspension bridges,there exists many engineering problems,such as,difficult construction,low efficiency,a mass of blind areas,and high security risks etc.The main cable large slope,large diameter full coverage,cable clamps and ancillary structural barriers are the main difficulties in achieving intelligent detection.Herein,we present a creeping-type inspection robot for automatic inspecting main cables called“CCRobot-M”via imitating biological climbing locomotion.The handrail ropes of the main cables acted as the railways for robot grasping.Two groups of holding boots were alternately opened and closed for crawling.An array of visual sensors were equipped for the omni-directional surface inspection of main cables.We analyzed the mechanical characteristics and locomotion capability of this climbing system,and verified its applicability and reliability in the experiment on a real bridge.The results demonstrated that CCRobot-M could climb smoothly on the main cables,move over the cable clamps,and obtain the full coverage view of inspection images.
作者 元小强 丁宁 陈斌 王鹏 赵敏 李德程 王超 YUAN Xiaoqiang;DING Ning;CHEN Bin;WANG Peng;ZHAO Min;LI Decheng;WANG Chao(Shenzhen Institute of Artificial Intelligence and Robotics for Society,Guangdong Shenzhen 518129;The Chinese University of Hong Kong(Shenzhen)Institute of Robotics and Intelligent Manufacturing,Guangdong Shenzhen 518172;Chongqing Communications Technology Research&Design Institute,Chongqing 400067)
出处 《公路交通技术》 2023年第4期62-69,共8页 Technology of Highway and Transport
基金 国家重点研发计划项目(2019YFB1310403) 广东省基础与应用基础研究基金资助项目(2019A1515111119)。
关键词 机器人 悬索桥 主缆 视觉检测 robot suspension bridge main cable visual inspection
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