钛合金激光填丝焊缝晶粒生长及相变原位观察

熔池的图像处理与特征提取技术是船舶熔化极气体保护焊(gas metal arc welding, GMAW)智能化焊接质量监控的重要内容，针对船体板GMAW焊接过程中的烟雾大、飞溅多等不稳定特性导致熔池图像采集模糊、边缘提取困难等问题，提出一种基于均值漂移(mean shift, MS)优化模糊C均值聚类(fuzzy c-means, FCM)的图像处理算法. 在优化设计焊接动态视觉传感系统中，以最大化保证图像信息采集清晰度的基础上，利用MS算法获取超像素图像以解决FCM算法对噪声的敏感性，同时在FCM算法上引入加权邻域窗口，以增强MS-FCM算法的鲁棒性，来克服烟雾、飞溅、弧光等噪声影响，进而完成图像分割与边缘提取. 最后，设计出关于FCM、空间约束模糊C均值聚类 (fuzzy c-means with spatial constraints, FCM_S)、加强型模糊聚类(enhanced fuzzy c-means, ENFCM)和模糊局部信息C均值聚类(fuzzy local information c-means clustering, FLICM)算法的4种不同图像处理方法，并与MS-FCM优化模型进行边缘分割效果对比，获取几种方法所提取的熔宽，验证熔池几何特征的提取精度. 结果表明，MS-FCM算法在船舶焊接熔池图像处理方面能有效抑制噪声干扰，平滑信息，达到较高的提取精度.

In-situ observation of grain growth and phase transformation in laser welding of titanium alloy with filler wire

The image processing and feature extraction technology of molten pool is an important part of intelligent welding quality monitoring for gas metal arc welding (GMAW) on ships. To address the unstable characteristics of large smoke and spatter during GMAW welding of ship hull plates, such as blurred image acquisition and difficult edge extraction, a fuzzy c-means clustering (FCM) based on mean shift (MS) optimization is proposed The image processing algorithm for In the optimization design of the welding dynamic visual sensing system, on the basis of maximizing the clarity of image information acquisition, the MS algorithm is used to obtain superpixel images to solve the sensitivity of the FCM algorithm to noise. At the same time, a weighted neighborhood window is introduced on the FCM algorithm to enhance the robustness of the MS-FCM algorithm, overcome the effects of smoke, spatter, arc light, noise, etc., and complete image segmentation and edge extraction Finally, four different image processing methods were designed for FCM, fuzzy c-means with spatial constraints (FCM-S), enhanced fuzzy c-means (ENFCM), and fuzzy local information c-means clustering (FLICM) algorithms. The edge segmentation effects were compared with the MS-FCM optimization model to obtain the extracted fusion widths from these methods, Verify the accuracy of extracting geometric features of the molten pool The results show that the MS-FCM algorithm can effectively suppress noise interference, smooth information, and achieve high extraction accuracy in ship welding pool image processing.