ZHANG Lingling, REN Panpan, XU Ao, ZHANG Jiran, DING Libin, AN Chaofeng, WU Song. On-Site Detection of Airtightness of Building Windows Based on Infrared Image Processing[J]. Infrared Technology , 2023, 45(4): 410-416.
Citation: ZHANG Lingling, REN Panpan, XU Ao, ZHANG Jiran, DING Libin, AN Chaofeng, WU Song. On-Site Detection of Airtightness of Building Windows Based on Infrared Image Processing[J]. Infrared Technology , 2023, 45(4): 410-416.

On-Site Detection of Airtightness of Building Windows Based on Infrared Image Processing

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  • Received Date: May 19, 2022
  • Revised Date: July 10, 2022
  • Current methods of on-site detection of airtightness of building windows cannot ensure that the airtightness grades of all windows satisfy the standard. Moreover, there is a lack of efficient and convenient detection methods. Thus, we proposed an on-site method to detect the airtightness performance level of windows. In this study, an infrared image of the windows is collected using a thermal imager, the abnormal area in the image is detected and the defect area is calculated, then an infrared detection model for window defects is established. Based on the experimentally measured indoor–outdoor temperature difference, the defect area of the window and air infiltration, a calculation model for the air infiltration of windows is built. The model is combined with the infrared detection model of exterior windows defects to obtain the air infiltration of the window, and the on-site detection of the windows airtightness performance is realized and then preliminary determine of whether the window meets the corresponding airtightness performance level, which improves the efficiency of the on-site inspection of the airtightness performance of windows and provides a new method for the on-site determination of the airtightness performance level of windows.
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