The study investigates the corrosion behavior of galvanized high-strength steel wire, which significantly affects the bearing capacity and residual fatigue life of cables in cable-supported bridges. Through standardized salt spray accelerated corrosion tests, steel wires with varying corrosion degrees are obtained. Three-dimensional laser scanning technology reconstructs the corroded wire surface, while image recognition techniques extract geometric characteristics of corrosion pits. Fitting expressions are established to correlate the minimum cross-sectional area, maximum pit depth and dip angle, and mass loss ratio of the wire. Statistical analysis reveals log-normal distributions for the lengths of major and minor axes of corrosion pits over time. Fitting curves for elongation after fracture, nominal yield strength, and nominal ultimate strength, along with elastic modulus distribution, are derived for different mass loss ratios. Comparing corrosion grading criteria, the study quantitatively describes corrosion characteristic parameters for distinct corrosion grades. These insights enhance understanding of corrosion behavior and mechanical property degradation in high-strength steel wires, offering a quantitative framework for assessing and classifying corrosion extent based on measurable parameters.

中文翻译：

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基于3D激光扫描和图像识别的桥梁索用镀锌高强钢丝腐蚀特性及评价

该研究调查了镀锌高强钢丝的腐蚀行为，该行为显着影响索承式桥梁中索的承载能力和残余疲劳寿命。通过标准化盐雾加速腐蚀试验，得到不同腐蚀程度的钢丝。三维激光扫描技术重建腐蚀线材表面，图像识别技术提取腐蚀坑的几何特征。建立拟合表达式来关联最小横截面积、最大凹坑深度和倾角以及线材的质量损失比。统计分析揭示了腐蚀坑长轴和短轴长度随时间的对数正态分布。对于不同的质量损失率，得出了断裂后伸长率、名义屈服强度和名义极限强度以及弹性模量分布的拟合曲线。通过比较腐蚀分级标准，该研究定量描述了不同腐蚀等级的腐蚀特征参数。这些见解增强了对高强度钢丝腐蚀行为和机械性能退化的理解，为根据可测量参数评估和分类腐蚀程度提供了定量框架。