基于红外图像增强算法的混凝土内部缺陷检测研究

Concrete Internal Defect Detection Based on Infrared Image Enhancement Algorithm

由于混凝土的不良导热性能,传统红外检测方法分辨率低、缺陷特征不明显。针对上述问题,研究了结合红外热像和增强图像算法的混凝土内部缺陷检测方法;开展了混凝土中不同深度、大小的缺陷的红外检测试验,并采用时域拟合与限制对比度直方图均衡算法相结合的方式对红外检测图像进行处理;对比了处理前后的热像图缺陷识别效果。试验结果表明:算法应用后缺陷识别所需温差从0.3℃降至0.1℃,边缘细节得到优化,提高了红外图像混凝土内部缺陷检测的精度和实用范围。该方法拓展了红外热像在混凝土无损检测中的应用范围。

The traditional infrared detection method has low resolution and its defect characteristics were not obvious on account of the poor thermal conductivity of concrete.In view of the problems above,a concrete internal defect detection method combining infrared thermal image and enhanced image algorithm was proposed.The infrared detection tests of concrete with defects of different depths and sizes were carried out.The infrared detection images were processed by means of combining time-domain fitting with CLAHE algorithm,and the defect recognition effects before and after processing were compared.The test results show that the temperature difference required for defect identification decreases from 0.3℃to 0.1℃after the application of algorithm and the edge details are optimized,which improves the accuracy and practical range of infrared image concrete internal defect detection.The proposed method expands the application range of infrared thermography in concrete nondestructive testing.