针对人工检测热障涂层形貌特征所具有的繁复性、误差大等缺点, 提出一种利用机器视觉自动化识别热障涂层形貌特征并计算形貌特征参数的方法. 完成了基于数学形态学的片层轮廓自动提取及铺展形貌参数的计算, 用最大类间方差法求取二值分割阈值, 运用均值滤波和形态学操作为图片去噪并保证单个片层的连通性, 通过轮廓提取来获得片层边缘信息, 最后根据所提取出的轮廓计算片层的实度参数. 同时, 进一步完成了基于遍历搜索的热障涂层中裂纹的自动识别及长度计算. 首先, 识别出图像中的片层并去除, 运用闭运算完成断裂裂纹的修复, 通过图像细化得到裂纹骨架; 然后, 遍历搜索每条裂纹, 完成长度计算. 结果表明, 采用所提出方法检测片层轮廓和识别裂纹的效果良好, 具有较好的抗噪声干扰能力, 可以精确计算出形貌特征参数, 对研究热喷涂熔滴在基材表面的沉积行为有重要的推动作用.

To address the shortcomings of manual detection of thermal barrier coating topographic features, such as complexity and large errors, a method for automatically identifying topographic features of thermal barrier coatings using machine vision and calculating topographic feature parameters is proposed in this study. First, splat contours are automatically extracted based on a mathematical morphology and calculation of spread morphological parameters. The maximum interclass variance method is next used to obtain the binary segmentation threshold and the median filter and morphological operations are used to denoise the image and ensure a single splat. The connectivity of the splat is then obtained by contour extraction, and the solidity parameter of the splat is finally calculated according to the extracted contour. Simultaneously, this study realizes automatic identification and length calculation of cracks in thermal barrier coatings based on a traversal search. First, the lamellae in the image are identified and removed, and the fractured crack is repaired by the closing operation. The cracked skeleton is next obtained through image refinement, and each crack is then traversed and searched to complete the length calculation. The results show that the method effectively detects the splat profile and identifies cracks, has a good anti-noise interference ability, and can accurately calculate topographic feature parameters. Thus, this method can play a critical role in promoting the study of the deposition behavior of thermal spray droplets on the surfaces of substrates.