In view of the difficulty of identifying internal micro corrosion-induced cracks in concrete and the poor accuracy of quantitative analysis, which results in inaccurate results regarding the law of formation of internal cracks, reinforced magnesium oxychloride cement concrete (RMOCC) was subjected to a galvanostatic acceleration test, and X-CT technology was combined with the support vector machines (SVM) identification algorithm and grey-level co-occurrence matrix (GLCM) theory. Using the SVM algorithm and GLCM theory, the internal average crack width of concrete and the contrast, correlation, angular second moment (ASM) and inverse difference moment (IDM), which characterise the change in slice texture information, were used as degradation parameters. Using the average internal crack width and IDM as the degradation index, a reliability degradation competition failure analysis was conducted to study RMOCC's law of internal crack formation. The results showed that the SVM algorithm had a greater than 95% accuracy in recognising cracks. In the entire corrosion-induced crack formation process, IDM and the average internal crack width values were consistent with the normal distribution. Through reliability degradation competition failure analysis between IDM and the average crack width value, the average crack width calculated with SVM is more suitable for the degradation analysis of internal corrosion-induced cracks in RMOCC.

中文翻译：

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钢筋氯镁水泥混凝土内腐蚀裂纹演化

针对混凝土内部微腐蚀裂纹识别困难，定量分析精度较差，导致内部裂纹形成规律结果不准确的问题，对增强氯镁水泥混凝土（RMOCC）进行了恒电流分析。加速测试，将X-CT技术与支持向量机（SVM）识别算法和灰度共生矩阵（GLCM）理论相结合。利用SVM算法和GLCM理论，以混凝土内部平均裂缝宽度以及表征切片纹理信息变化的对比度、相关性、角二阶矩（ASM）和反差分矩（IDM）作为退化参数。以平均内部裂纹宽度和IDM作为退化指标，进行可靠性退化竞争失效分析，研究RMOCC内部裂纹形成规律。结果表明，SVM算法识别裂纹的准确率大于95%。在整个腐蚀诱发裂纹形成过程中，IDM和平均内部裂纹宽度值均符合正态分布。通过IDM与平均裂纹宽度值之间的可靠性退化竞争失效分析，SVM计算的平均裂纹宽度更适合RMOCC内腐蚀裂纹的退化分析。在整个腐蚀诱发裂纹形成过程中，IDM和平均内部裂纹宽度值均符合正态分布。通过IDM与平均裂纹宽度值之间的可靠性退化竞争失效分析，SVM计算的平均裂纹宽度更适合RMOCC内腐蚀裂纹的退化分析。在整个腐蚀诱发裂纹形成过程中，IDM和平均内部裂纹宽度值均符合正态分布。通过IDM与平均裂纹宽度值之间的可靠性退化竞争失效分析，SVM计算的平均裂纹宽度更适合RMOCC内腐蚀裂纹的退化分析。