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

1.School of Civil Engineering, Southwest Jiaotong University, Chengdu 610031, P. R. China;2.Sichuan Provincial Architectural Design and Research Institute Co. Ltd., Chengdu 610095, P. R. China;3.Southwest Jiaotong University Chengdu Design Institute Co. Ltd., Chengdu 610031, P. R. China

Clc Number:

TU18

Fund Project:

National Natural Science Foundation of China (No. 52308330); Research Project of Sichuan Provincial Architectural Design and Research Institute Co. Ltd. (No. KYYN202231-F1)

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    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.

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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

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History
  • Received:May 13,2024
  • Revised:
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  • Online: November 03,2025
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