开发一种利用无人机收集混凝土表面裂缝图像以评估桥梁结构健康的解决方案

IF 2.7 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS
B. Ngo, Chieu X. Luong, Long Ngo, H. M. Luong
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引用次数: 0

摘要

摘要:本研究提供了一种有效的方法来评估混凝土桥梁的结构完整性,即利用无人机收集表面裂缝和缺陷的图像。使用无人机收集裂纹样本减少了人为错误,适用于恶劣的工作条件和短时间的检查。本文基于无人机安全观看距离的飞行准则和兴趣点的概念,提出了一种新的典型飞行路径的兴趣点飞行算法。在这项研究中,无人机的飞行控制器与树莓Pi4相结合,建立和改变适合任务的典型飞行路径,并增加了控制飞行模式切换、分离和自动返回原始轨道的交互功能,以满足专家指定的poi。换句话说,当无人机接近需要图像捕捉的区域时,它们会自动移动到一个安全距离拍摄裂缝,然后返回预定的轨道。在Cau May大桥上进行的一项实验表明,在嵌入式计算机上创建的路径规划算法可以成功地协调飞行控制器在检查过程中切换三次悬停和放大裂缝。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Development of a solution for collecting crack images on concrete surfaces to assess the structural health of bridges using drone
ABSTRACT This study contributes an efficient method for assessing the structural integrity of concrete bridges by collecting images of surface cracks and defects with drones. The use of drones to gather crack samples reduces human error and is appropriate in adverse working conditions and short-duration examinations. This work introduces a new POI (Points of Interest) flying algorithm for typical flight paths, based on the drone flying criteria of safe viewing distance and the POI concept. In this research, the flight controller of the drone was combined with a Raspberry Pi4 to build and alter a typical flight path suitable for the mission, with the addition of interactive features that control flight mode switching, separation, and automatic return to the original orbit to meet expertly specified POIs. In other words, as drones approach a region requiring image capture, they automatically move to a safe distance to photograph cracks and then return to their predetermined orbit. An experiment at the Cau May bridge demonstrates that the path-planning algorithms created on an embedded computer can successfully coordinate with the flight controller switching three times to hover and zoom in on fractures during the inspection.
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来源期刊
CiteScore
7.50
自引率
0.00%
发文量
18
审稿时长
27 weeks
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