Unsupervised Recognition and Characterization of the reflected Laser Lines for Robotic Gas Metal Arc Welding
文献类型：期刊论文
| 作者 | Wang ZZ(王振洲)
|
| 刊名 | IEEE Transactions on Industrial Informatics
 |
| 出版日期 | 2017 |
| 页码 | 1-11 |
| 关键词 | Image processing clustering gradient detection segmentation spline threshold selection |
| ISSN号 | 1551-3203 |
| 产权排序 | 1 |
| 通讯作者 | 王振洲 |
| 中文摘要 | Unsupervised recognition of the reflected laser lines from the arc light modified background is prerequisite for the subsequent measurement and characterization of the weld pool shape, which is of great importance for the modeling and control of robotic arc welding. To facilitate the unsupervised recognition, the reflected laser lines need to be segmented as accurate as possible, which requires the segmented laser lines to be as continuous as possible to decrease the adverse effect of the noise blobs. In this paper, the intensity distribution caused by the arc light in the captured image is modeled. Based on the model, an efficient and robust approach is proposed and it comprises six parts: (1) reduction of the uneven image background by a difference operation; (2) spline enhancement to remove the fuzziness; (3) a gradient detection filter to eliminate the uneven background further; (4) segmentation by an effective threshold selection method; (5) removal of the noise blobs adaptively; (6) clustering based on the on-line computed slope of the laser line. After the laser line is clustered, a second order polynomial is fitted to it. Finally, the weld pool is characterized by the parameters of the clustered laser line and its fitted polynomial. Experimental results verified that the proposed approach for unsupervised reflected laser line recognition is significantly superior to state of the art approach in recognition accuracy. |
| 语种 | 英语 |
| 源URL | [http://ir.sia.cn/handle/173321/20239]  |
| 专题 | 沈阳自动化研究所_机器人学研究室 |
| 推荐引用方式 GB/T 7714 | Wang ZZ. Unsupervised Recognition and Characterization of the reflected Laser Lines for Robotic Gas Metal Arc Welding[J]. IEEE Transactions on Industrial Informatics,2017:1-11. |
| APA | Wang ZZ.(2017).Unsupervised Recognition and Characterization of the reflected Laser Lines for Robotic Gas Metal Arc Welding.IEEE Transactions on Industrial Informatics,1-11. |
| MLA | Wang ZZ."Unsupervised Recognition and Characterization of the reflected Laser Lines for Robotic Gas Metal Arc Welding".IEEE Transactions on Industrial Informatics (2017):1-11. |
入库方式： OAI收割
来源：沈阳自动化研究所
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