metallographic image – hardness (HV) – corrosion potential (Ecorr)

The use of metallographic images to predict the mechanical properties of materials and their corrosion behavior is helpful in achieving nondestructive detection and quality control. Taking extruded Al-Zn-Mg alloys with different surface microstructures as example materials, 4,800 sets of “metallographic image – hardness (HV) – corrosion potential (Ecorr)” data were experimentally collected to establish accurately correlate the metallographic images, mechanical property, and corrosion behavior, which can provide theoretical support for intelligent and nondestructive testing methods of engineering materials.

利用金相图像预测材料的力学性能及其腐蚀行为，有助于实现非破坏性检测与质量控制。以具有不同表面微观结构的挤压态Al-Zn-Mg合金为示例材料，通过实验采集了4800组‘金相图像–硬度（HV）–腐蚀电位（Ecorr）’数据，旨在准确建立金相图像、力学性能与腐蚀行为之间的关联，为工程材料的智能非破坏性测试方法提供理论支撑。