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建筑饰面砖空鼓缺陷无人机识别关键参数试验研究

赵仕兴 马麟涛 许浒 田永丁 何佳斌 余志祥

土木与环境工程学报(中英文)2025,Vol.47Issue(5):97-109,13.
土木与环境工程学报(中英文)2025,Vol.47Issue(5):97-109,13.DOI:10.11835/j.issn.2096-6717.2024.086

建筑饰面砖空鼓缺陷无人机识别关键参数试验研究

Experimental study on key parameters for identification of hollowing defects via UAV in facade tiles

赵仕兴 1马麟涛 2许浒 3田永丁 2何佳斌 2余志祥2

作者信息

  • 1. 西南交通大学 土木工程学院,成都 610031||四川省建筑设计研究院有限公司,成都 610095
  • 2. 西南交通大学 土木工程学院,成都 610031
  • 3. 西南交通大学 土木工程学院,成都 610031||成都西南交通大学设计研究院有限公司,成都 610031
  • 折叠

摘要

Abstract

To mitigate the safety hazards posed by the frequent detachment of facade tiles,this study summarized the causes of these defects,identifying hollowing defects as precursors to exterior wall tile detachment.Using an Unmanned Aerial Vehicle(UAV)equipped with infrared thermal imaging camera,the study conducted laboratory tests for hollowing detection.The optimal observation attitude of the UAV was investigated.The impact of defect characteristic parameters on identification accuracy and the effect of UAV rotor operation on the temperature of external walls were evaluated.Additionally,a temperature difference threshold was proposed for the identification of hollowing in exterior wall facade tiles.The study indicated that optimal observation occurs when the UAV is 2 to 3 meters from the external wall,with a vertical angle of-30° to 30° and a horizontal angle of-15° to 15°.The drone rotors increase the cooling rate of external walls by 10%.Recognition improves with hollowing of larger sizes,shallower depths,and greater thicknesses.Hollowing defects in black and red tiles exhibited higher temperatures,while those in yellowish tiles exhibited lower temperatures.Consequently,an outdoor test was conducted to verify the efficacy of the proposed detection method by comparing it with visible light image recognition,which provides a novel threshold for the expeditious identification of hollowing defects in facade tiles.

关键词

高坠事故/建筑维护/外立面缺陷/空鼓缺陷/无人机/红外热成像法

Key words

fall accident/building maintenance/facade defects/hollowing defects/UAV/infrared thermogra-phy method

分类

建筑与水利

引用本文复制引用

赵仕兴,马麟涛,许浒,田永丁,何佳斌,余志祥..建筑饰面砖空鼓缺陷无人机识别关键参数试验研究[J].土木与环境工程学报(中英文),2025,47(5):97-109,13.

基金项目

国家自然科学基金(52308330) (52308330)

四川省建筑设计研究院有限公司科研项目(KYYN202231-F1)National Natural Science Foundation of China(No.52308330) (KYYN202231-F1)

Research Project of Sichuan Provincial Architectural Design and Research Institute Co.Ltd.(No.KYYN202231-F1) (No.KYYN202231-F1)

土木与环境工程学报(中英文)

OA北大核心

2096-6717

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