The Study on Thickness Detection Technology of Reflective Thermal Insulation Coatings for Buildings Based on Hyperspectral Technology
LI Xiao-fang1, WANG Yan-cang2, 3*, GU Xiao-he4, WANG Li-mei1, LI Xiao-peng1, FENG Hua2, CHEN Ting-yu2
1. Langfang Normal University,Langfang 065000,China
2. North China Institute of Aerospace Engineering,Langfang 065000, China
3. School of Traffic and Transportation, Shijiazhuang Tiedao University, Shijiazhuang 050043, China
4. Beijing Research Center for Information Technology in Agriculture, Beijing 100097, China
Abstract:As a new type of building coatings, reflective heat insulation coatings have been widely used in building construction by virtue of its advantages of energy saving and environmental protection. The high and low performance of reflective heat insulation coatings directly affects the performance of building energy saving and environmental protection, and has a great impact on the indoor environment of buildings. Reflective thermal insulation coatings for buildings mainly achieve energy saving and environmental protection by reflecting and absorbing solar radiation (visible-near infrared) and building radiation (thermal infrared). For specific building reflective heat insulation coatings, the interaction between them and light mainly depends on the construction parameters, such as coating thickness. Therefore, hyperspectral technology is used to quantitatively analyze the reflection and absorption characteristics of building reflective heat insulation coatings, and to study the influence of coating construction parameters (thickness) on the performance of building reflective heat insulation coatings, so as to provide scientific and technological support for coating construction detection. With the help of hyperspectral technology, this study measured the spectral data of different coatings thickness, analyzed the evolution law of the spectral characteristics of coatings with the increase of the thickness of coatings, studied the coatings index which can characterize the thickness of coatings construction, and analyzed the correlation between the spectral data of coatings and the coatings index constructed by them and the thickness of coatings respectively. Selecting and screening the sensitive indicators of coatings construction thickness, building the thickness detection model of coatings construction, and searching for the method suitable for the thickness detection of coatings construction. The results show that: (1) the spectral data located in the 420~1 070 nm range are sensitive to the thickness of coatings 0.1~2.5 mm, and the correlation coefficient r with the thickness of coatings construction is high and phase-wise. For stability, it shows that the spectral range is sensitive to the thickness of coatings and can be used to detect the thickness of coatings; (2) Compared with the original spectrum, the coating index can effectively enhance the sensitivity of the spectrum to the thickness of coatings, and the RCI index constructed from 484 and 479 nm is the best parameter to characterize the thickness of coatings in the five categories of coatings index; (3) Among the five kinds of coatings indices, the model based on RCI index has the highest accuracy and is the best one, and its R2=0.973, RMSE=0.185, RPD=4.018.
李笑芳,王延仓,顾晓鹤,王丽玫,李晓鹏,冯 华,陈亭宇. 基于高光谱技术建筑反射隔热涂料厚度检测技术的研究[J]. 光谱学与光谱分析, 2020, 40(08): 2552-2557.
LI Xiao-fang, WANG Yan-cang, GU Xiao-he, WANG Li-mei, LI Xiao-peng, FENG Hua, CHEN Ting-yu. The Study on Thickness Detection Technology of Reflective Thermal Insulation Coatings for Buildings Based on Hyperspectral Technology. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2020, 40(08): 2552-2557.
[1] Kaynakli O. Renewable and Sustainable Energy Reviews, 2012, 16(1): 415.
[2] Shi H, Zou X, Wang X. Physics of Plasmas, 2017, 24(7): 5063.
[3] Modeste Kameni Nematchoua, Chrysostôme R R,Raminosoa, et al. Renewable and Sustainable Energy Reviews, 2015, 50: 1192.
[4] TANG Wan-ping, DING Jing-jie, LI Gong-ping, et al(唐万平, 丁晶洁, 李公平, 等). Paint & Coatings Industry(涂料工业), 2018, 48(12): 47.
[5] BAO Chu-cai, LIU Fu-jian, LIU Qiong,et al(包楚才, 刘付建, 刘 琼, 等). Physical Testing and Chemical Analysis·Part B: Chemical Analysis(理化检验·化学分册), 2016, 52(10): 1178.
[6] HE Yan, ZHANG Xiong, GUAN Jian(何 燕, 张 雄, 管 建). Journal of Building Materials(建筑材料学报), 2015, 18(5): 784.
[7] MA Yi-ping, LI Kui, WANG Cui,et al(马一平, 李 奎, 王 翠, 等). Journal of Tongji University·Natural Science(同济大学学报·自然科学版), 2017, 45(2): 249.
[8] YANG Guang, DENG An-zhong(杨 光, 邓安仲). Surface Technology(表面技术), 2017, 46(11): 260.
[9] Yuan L, Han A, Ye M, et al. Solar Energy, 2018, 163: 453.
[10] LIN Mei(林 美). Polymer Materials Science & Engineering(高分子材料科学与工程), 2017, 33(3): 168.
[11] WANG Yan-cang, JIN Yong-tao, WANG Xiao-ning(王延仓, 金永涛, 王晓宁). Spectroscopy and Spectral Analysis(光谱学与光谱分析), 2018, 38(8): 2571.
[12] Liu F, Rossiter D C, Song X D, et al. Geoderma, 2016, 263:254.