1 School of Materials Science and Engineering, Southeast University, Nanjing 211189, China 2 Research Center of Green Building and Construction Materials, Southeast University, Nanjing 211189, China 3 China Railway Construction Group Co.,Ltd., Beijing 100040, China 4 China Railway Construction Engineering Group Co., Ltd., Beijing 100160, China 5 China Railway 12th Bureau Group Co., Ltd., Taiyuan 030024, China
Abstract: In order to solve the problem of inefficiency and error caused by manual measurement and empirical evaluation in the quality inspection of fair-faced concrete projects, this paper presents a quantitative analysis method for the appearance quality of fair-faced concrete. The method was based on the UAV and the orbital large format scanner to collect the appearance image of concrete efficiently. The enhanced pore edge morphological parameters were extracted accurately by HiGauss, Sobel and Erode filters to accurately identify and to calculate APAR (appearance pore area ratio). SDCA (standard deviation of chromatic aberration)and SDR (standard deviation from RAL)were proposed to characterize the chromatic aberration of fair-faced concrete. The robustness of the method was verified based on light intensity and surface moisture content, and has been successfully applied to the preliminary quality acceptance of fair-faced concrete in Xiong'an Station of Beijing-Xiong'an Intercity Railway and Chaoyang Station of Beijing-Shenyang high-speed Railway. With the variation of light intensity, the average floating deviation of APAR of the same component was 4.82%, and the maximum deviation from manual measurement was 5.84%. The average floating deviation of SDCA of the same component was 8.60%, and the maximum floating deviation was 10.35%. The average floating deviation of SDR of the same component was 8.97%, and the maximum floating deviation was 13.58%. With the variation of surface moisture content, the average floating deviation of APAR of the same component was 9.03%, the maximum floating deviation was 9.16%, and the maximum deviation from manual measurement was 11.24%. The average floating deviation of SDCA of the same component was 6.55%, the maximum floating deviation was 8.27%, and the ave-rage floating deviation of SDR of the same component was 6.80%, and the maximum floating deviation was 10.11%. For the fair-faced concrete images collected by UAV, too much or too little light intensity would adversely affect the accuracy of the appearance quality analysis. As the surface moisture content increased, the three parameters all showed a downward trend, indicating that when drying, the difference in appearance quality was the most obvious. This method could provide timely supervision and feedback to the construction process, and had the advantages of high efficiency, quantification and automation.
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