This paper presents an Automated Crack Detection and Measurement (ACDM) method, which is based on the strain field obtained by the Digital Image Correlation (DIC) method and uses machine vision recognition to quickly obtain the distribution of cracks on the surface of the specimen in the corresponding damage state. Through three-point bending test, the Crack Mouth Opening Displacement (CMOD) value is obtained by the clip gauge and ACDM method, respectively. The CMOD was measured by the clip gauge as a reference. By analyzing the accuracy of this method, the results show that when CMOD was less than 0.05 mm, the identification error is less than 0.01 mm, and ACDM can be used to analyze the micro-crack concrete damage. Based on the compression tests of three groups of concrete cube specimens under different damage stages, the damage indexes obtained by ACDM method have corresponding numerical changes greater than 10-3, which is more sensitive and accurate than the current quantitative Cv-value of strain field.
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WANG Qingyuan, XU Ying?,QIAN Sheng.基于机器视觉和数字图像相关技术的混凝土损伤演化研究[J].湖南大学学报:自然科学版,2023,(11):169~180