Wójcicka Anna, Walusiak Łukasz, Mroczka Krzysztof, Jaworek-Korjakowska Joanna Krystyna, Oprzędkiewicz Krzysztof, Wrobel Zygmunt
Department of Automatic Control and Robotics, AGH University of Science and Technology, 30-059 Cracow, Poland.
Faculty of Architecture, Civil Engineering and Applied Arts, University of Technology, Rolna 43, 40-555 Katowice, Poland.
Materials (Basel). 2022 Jan 31;15(3):1129. doi: 10.3390/ma15031129.
Friction stir welding (FSW) is an environmentally friendly, solid-state welding technique. In this research work, we analyze the microstructure of a new type of FSW weld applying a two- stage framework based on image processing algorithms containing a segmentation step and microstructure analysis of objects occurring in different layers. A dual-speed tool as used to prepare the tested weld. In this paper, we present the segmentation method for recognizing areas containing particles forming bands in the microstructure of a dissimilar weld of aluminum alloys made by FSW technology. A digital analysis was performed on the images obtained using an Olympus GX51 light microscope. The image analysis process consisted of basic segmentation methods in conjunction with domain knowledge and object detection located in different layers of a weld using morphological operations and point transformations. These methods proved to be effective in the analysis of the microstructure images corrupted by noise. The segmentation parts as well as single objects were separated enough to analyze the distribution on different layers of the specimen and the variability of shape and size of the underlying microstructures, which was not possible without computer vision support.
搅拌摩擦焊(FSW)是一种环境友好型的固态焊接技术。在本研究工作中,我们基于包含分割步骤和不同层中出现的物体的微观结构分析的图像处理算法,运用两阶段框架分析了一种新型搅拌摩擦焊焊缝的微观结构。使用双速工具制备测试焊缝。在本文中,我们提出了一种分割方法,用于识别由搅拌摩擦焊技术制造的铝合金异种焊缝微观结构中包含形成条带的颗粒的区域。对使用奥林巴斯GX51光学显微镜获得的图像进行了数字分析。图像分析过程包括结合领域知识的基本分割方法,以及使用形态学操作和点变换对位于焊缝不同层中的物体进行检测。这些方法在分析受噪声干扰的微观结构图像时被证明是有效的。分割部分以及单个物体被充分分离,以便分析试样不同层上的分布以及底层微观结构的形状和尺寸变化,而没有计算机视觉支持这是不可能实现的。