首页> 外文OA文献 >A laser back-lighting based metal transfer monitoring system for robotic gas metal arc welding
【2h】

A laser back-lighting based metal transfer monitoring system for robotic gas metal arc welding

机译:基于激光背光的金属气体自动电弧焊金属转移监测系统

摘要

Gas metal arc welding (GMAW) can be considered the most widely used process in automated welding due to its high productivity. However, its solid to liquid metal transfer also complicates the process and causes fumes and spatters. It needs to be better understood and controlled for assured weld quality, improved process stability, and reduced fumes, spatters, and energy consumption. For automated robotic gas metal arc welding, automatic and efficient image processing algorithms are required to extract the metal transfer robustly. In addition, the machine vision apparatus in real welding environments should be compact and easy to handle. To this end, a simplified laser back-lighting based monitoring system is proposed to measure the metal transfer in this paper. To facilitate the image analysis, the arc light and the image are modeled based on the physical laws. A double-threshold method is proposed to segment the image robustly with a linear membership assigned to the fuzzy edge region. To compute the two thresholds accurately and simultaneously, slope difference is calculated for the histogram distribution and the gray-scale positions with the largest and second largest peaks are selected as the two thresholds respectively. Experimental results verified the effectiveness of the on line monitoring system and the subsequent automatic image processing methods. © 2015 Elsevier Ltd.All rights reserved.
机译:气体保护金属电弧焊(GMAW)具有高生产率,可以被认为是自动焊接中使用最广泛的工艺。但是,其从固态到液态金属的转移也使过程复杂化,并产生烟雾和飞溅。需要更好地理解和控制焊缝,以确保焊接质量,改善工艺稳定性并减少烟尘,飞溅和能耗。对于自动化的机器人气体金属电弧焊,需要自动而有效的图像处理算法来稳健地提取金属转移。此外,真实焊接环境中的机器视觉设备应紧凑且易于操作。为此,本文提出了一种简化的基于激光背光的监测系统来测量金属的迁移。为了促进图像分析,基于物理定律对弧光和图像进行建模。提出了一种双阈值方法,利用分配给模糊边缘区域的线性隶属度对图像进行鲁棒分割。为了准确而同时地计算两个阈值,计算直方图分布的斜率差,并将具有最大和第二最大峰值的灰度位置分别选择为两个阈值。实验结果证明了在线监控系统和后续自动图像处理方法的有效性。 ©2015 Elsevier Ltd.保留所有权利。

著录项

  • 作者

    Wang ZZ(王振洲);

  • 作者单位
  • 年度 2016
  • 总页数
  • 原文格式 PDF
  • 正文语种
  • 中图分类

相似文献

  • 外文文献
  • 中文文献
  • 专利

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号