基于改进主动轮廓模型的强噪声焊缝识别方法  

Weld Seam Recognition Method under Strong Noise Based on Improved Active Contour Model

作　　者：周毅 章国宝[1] ZHOU Yi;ZHANG Guobao(School of Automation,Southeast University,Nanjing 211189,China)

机构地区：[1]东南大学自动化学院,江苏南京211189

出　　处：《热加工工艺》2025年第3期30-34,40,共6页Hot Working Technology

基　　金：江苏省社会发展项目(BE2020116)。

摘　　要：基于结构光视觉的焊缝跟踪系统被广泛应用于机器人焊接之中,而保障此类焊接作业质量的关键在于焊缝识别的精度。传统的焊缝识别算法往往难以解决强焊接噪声的干扰问题,为此提出了一种基于改进主动轮廓模型的焊缝识别算法。首先为了克服传统主动轮廓模型手动获取初始轮廓的缺点,设计了一种基本的分割算法来自动提取初始轮廓。接着根据强噪声焊缝图像的灰度分布特征,采用该算法对传统主动轮廓模型的能量函数进行了优化,并将拓展的结构张量添加至外部能量项,确保收敛结果的稳定与准确。最后,基于多段直线拟合和RANSAC直线拟合完成焊缝特征点的提取。实验表明:在强噪声干扰下,该算法具有良好的适准确性。The seam tracking system based on structured light vision is widely used in robot welding,and the key to ensure the quality of such welding is the accuracy of seam recognition.Traditional weld seam recognition algorithms can hardly solve the interference problem of strong welding noise,so a weld seam recognition algorithm based on improved active contour model was proposed.Firstly,in order to overcome the shortcomings of manually obtaining the initial contour by traditional active contour model,a basic segmentation algorithm to automatically extract the initial contour was designed.Then,according to the grayscale distribution characteristics of the weld image with strong noise,the algorithm was used to optimize the energy function of the traditional active contour model,and the extended structure tensor was added to the external energy term to ensure the stability and accuracy of the convergence result.Finally,the weld feature points were extracted based on multi-segment line fitting and RANSAC line fitting.The results show that the algorithm has good adaptive accuracy under strong noise interference.

关 键 词：焊缝识别 抗干扰 主动轮廓模型 结构张量 直线拟合 

分 类 号：TG409[金属学及工艺—焊接]