基于图像的腐蚀损伤及疲劳寿命研究

在实验室环境下,对航空LY12CZ铝合金试件进行了腐蚀试验,然后采用图像处理的方法,提取了孔蚀率、点蚀坑分形维数、点蚀坑半径3种腐蚀形貌特征值,通过灰色预测方法对腐蚀形貌特征值与腐蚀损伤之间的关系进行了研究,得到了基于形貌特征值的GM(1,3)腐蚀损伤预测模型。在此基础上,利用AFGROW软件建立了断裂力学模型,对不同腐蚀形貌特征条件下LY12CZ试件的疲劳寿命进行了计算与讨论。结果表明,试件的疲劳寿命与其表面腐蚀形貌密切相关,3种腐蚀形貌特征值均与试件的疲劳寿命负相关。此外,基于腐蚀形貌特征值计算得到的疲劳寿命值与利用实测点蚀坑深度计算得到的疲劳寿命值吻合较好,平均相对误差为8.84%。

Analysis of Corrosion Damage and Fatigue Life Based on Corrosion Image

Corrosion morphology image is one of the most important features for the evaluation of the corrosivity of a material. By means of an optical microscope, the corrosion morphology images as well as the pit depths of LY12CZ samples exposed to experimental environments are captured. After digital image processing, the color types of these images are transformed, and then three kinds of corrosion morphology characteristics are extracted. By using a GM (1,3) grey model, the relationship between the features of corrosion morphology images and pit depths are studied, and a model based on the morphology characteristics is established which can predict the pit depth. Based on this model, a fracture mechanics method which treated pitting as cracks is established by the software AFGROW, which is used to predict the fatigue life of LY12CZ samples. The results show that there is good agreement between the measured pit sizes and the predicted data based on the grey model. Moreover, the fatigue lives calculated based on corrosion morphology characteristics are reasonable as compared with the results calculated according to experimental data, the average relative error being 8.84%.