基于红外图像处理的建筑外窗气密性能现场检测

张玲玲; 任攀攀; 许廒; 张继冉; 丁立斌; 安朝封; 吴松

基于红外图像处理的建筑外窗气密性能现场检测

1.
烟台大学建筑学院, 山东烟台 264005
2.
中铁建工集团第二建设有限公司, 山东青岛 266112
3.
烟台东方能源科技有限公司, 山东烟台 264005

基金项目:

烟台大学研究生科技创新基金资助项目 KGIFYTU2235

详细信息

作者简介:
张玲玲（1972-），女，教授，研究方向：建筑节能与绿色建筑，E-mail: 305125954@qq.com

中图分类号: TU111.4
计量
- 文章访问数: 165
- HTML全文浏览量: 50
- PDF下载量: 30
- 被引次数: 0
出版历程
- 收稿日期: 2022-05-20
- 修回日期: 2022-07-11
- 刊出日期: 2023-04-20

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

1.
School of Architecture, Yantai University, Yantai 264005, China
2.
China Railway Construction Engineering Second Construction Co., Ltd., Qingdao 266112, China
3.
Yantai Dongfang Energy Technology Co., Ltd., Yantai 264005, China

摘要

摘要: 针对目前建筑外窗气密性现场检测方法无法保证其所有安装外窗的气密性等级全部达标，同时缺乏高效、便捷的检测手段，提出一种外窗气密性能等级现场检测方法，通过热像仪对外窗进行红外图像采集，对图像中的异常区域进行缺陷检测并计算缺陷面积，建立外窗缺陷红外检测模型。根据实验测得的室内外温差、外窗缺陷面积、空气渗透量，建立外窗空气渗透量计算模型，将此模型与外窗缺陷红外检测模型结合求得窗户的空气渗透量，实现外窗气密性能的现场检测，初步判定外窗是否符合相应的气密性能等级，提高了外窗气密性能现场检测的效率，为外窗气密性能等级现场判定提供一种新的途径。
- 红外图像 /
- 外窗气密性 /
- 缺陷面积计算 /
- 现场检测 /
- 空气渗透量
Abstract: 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.
- infrared image /
- airtightness of building windows /
- defect area calculation /
- on-site inspection /
- air infiltration amount

HTML全文

图 1 外窗红外图像预处理结果

Figure 1. Infrared image preprocessing results of window

下载: 全尺寸图片幻灯片

图 2 各方法进行外窗缺陷检测结果

Figure 2. Detect results of the defects of windows by various methods

下载: 全尺寸图片幻灯片

图 3 外窗缺陷实验值与图像处理值的散点图

Figure 3. Scatter plot of the experimental value and the image processing value of the window defect

下载: 全尺寸图片幻灯片

图 4 外窗空气渗透量计算模型神经网络回归分析

Figure 4. Regression analysis diagram of calculating model of air infiltration amount of windows with neural network

下载: 全尺寸图片幻灯片

图 5 外窗原始红外图像

Figure 5. Original infrared image of the window

下载: 全尺寸图片幻灯片

图 6 外窗缺陷检测图像

Figure 6. Defect detection image of the window

下载: 全尺寸图片幻灯片

表 1 外窗缺陷面积对比

Table 1. Defect area comparison of windows

Windows	Value of experiment/cm²	Roberts/cm²	Sobel/cm²	Prewitt/cm²	Canny/cm²	Log/cm²	Threshold value segmentation/cm²
C0407（1）	0.90	0.96	1.39	1.39	1.70	1.62	0.92
C0407（2）	1.50	1.50	1.80	1.80	1.40	2.10	1.50
C0709（1）	3.20	3.21	4.03	3.84	3.46	4.48	3.65
C0814（1）	4.30	5.19	11.32	11.07	6.58	11.61	4.70
C1218（1）	11.20	11.50	14.44	14.40	15.44	7.20	11.52
C1218（2）	10.30	11.03	14.22	14.02	10.89	14.76	10.43
C1716（1）	9.20	9.30	11.92	11.90	9.32	4.96	9.30
C2114（1）	15.80	14.86	25.42	24.88	22.93	23.33	16.87
C2114（2）	11.50	13.80	17.20	17.00	13.80	16.30	13.90
C2418（1）	20.90	24.60	31.80	31.40	23.40	26.90	24.60

下载: 导出CSV

表 2 各处理方式误差汇总

Table 2. Summary of errors of each processing method

Roberts	Sobel	Prewitt	Canny	Log	Threshold segmentation
7.36%	56.21%	53.86%	26.35%	61.92%	7.97%

下载: 导出CSV

表 3 外窗气密性能等级现场判定结果对比

Table 3. Comparison of site judgment results of airtightness performance grade of windows

Windows	Experimental result		Model result		Relative error
Windows	Air permeability/(m³/h)	Air permeability per unit area/(m³/(m²·h))	Air permeability/(m³/h)	Air permeability per unit area/(m³/(m²·h))	Relative error
C0923	7.00	3.38	7.32	3.54	4.60%
C0918	6.00	3.70	5.76	3.55	3.94%
C1823	17.00	4.11	18.28	4.41	7.41%
C0910	4.00	4.44	3.93	4.36	1.69%
C0623	5.00	3.62	5.13	3.72	2.69%
C0924	7.00	3.24	7.11	3.29	1.62%
C1523	12.00	3.48	13.06	3.78	8.76%
C1824	14.00	3.24	15.08	3.49	7.77%
C1822	17.00	4.29	17.74	4.48	4.41%
C1514	8.00	3.81	8.10	3.86	1.22%

下载: 导出CSV

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