A practical method for weld seam position detection
文献类型:会议论文
作者 | Qu RX(屈润鑫)![]() ![]() ![]() |
出版日期 | 2014 |
会议名称 | 2014 IEEE International Conference on Robotics and Biomimetics, IEEE ROBIO 2014 |
会议日期 | December 5-10, 2014 |
会议地点 | Bali, Indonesia |
页码 | 2558-2563 |
通讯作者 | 朱思俊 |
中文摘要 | Weld seam position detection mainly relies on initial point detection of weld seam in robotic welding automation. In industry factory, the position data for weld seam are usually detected through contact measurement sensor before welding. Such a method is not suitable in heavy industry, since length of weld seam may reach to ten meters which results in time-consuming position detection which will reduce the duty cycle of the equipment and lowered the cost-effective of welding equipment significantly. To satisfy the huge demand of market in industries mentioned above, a method based on scanning-spotlights and calibration technique with laser range finder sensors is proposed in this paper. The duty cycle of the equipment is improved significantly through separating welding motion system and weld seam position detection system. It not only meets welding position precision requirement, but also reduces the costs considerably. Moreover, the cost-effective is improved significantly. |
收录类别 | EI ; CPCI(ISTP) |
产权排序 | 1 |
会议主办者 | Harbin Institute of Technology; IEEE Robotics and Automation Society; National University of Defense Technology; Shenzhen Institutes of Advanced Technology, CAS; State Key Laboratory of Robotics and Systems |
会议录 | 2014 IEEE International Conference on Robotics and Biomimetics, IEEE ROBIO 2014
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会议录出版者 | IEEE |
会议录出版地 | Piscataway, NJ, USA |
语种 | 英语 |
ISBN号 | 978-1-4799-7396-5 |
WOS记录号 | WOS:000380399500429 |
源URL | [http://ir.sia.ac.cn/handle/173321/16110] ![]() |
专题 | 沈阳自动化研究所_装备制造技术研究室 |
推荐引用方式 GB/T 7714 | Qu RX,Zhu SJ,An XW,et al. A practical method for weld seam position detection[C]. 见:2014 IEEE International Conference on Robotics and Biomimetics, IEEE ROBIO 2014. Bali, Indonesia. December 5-10, 2014. |
入库方式: OAI收割
来源:沈阳自动化研究所
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