Tandem gas metal arc welding （ T-GMAW） process shows a high deposition rate that up to three times o f the single electrode GMAW, so the welding speed could be significantly increased in this process. H...Tandem gas metal arc welding （ T-GMAW） process shows a high deposition rate that up to three times o f the single electrode GMAW, so the welding speed could be significantly increased in this process. However, the majority o f this process applications are based on the pre-programmed robotic welding, which does not allow them to track the seam real-time during welding. Rotating arc sensor, sensing the seam position by detecting the changing of welding currents, has been widely adopted in the automatic robot welding process. It is proposed in this paper to integrate the rotating arc sensor with a trailing torch to develop a new approach of rotating arc lead tandem gas metal arc welding （RLT-GMAW） process. The characteristics of the welding currents in the proposed new welding process were firstly studied, and then a self-turning fuzzy control seam tracking strategy was developed for the mobile robot automatic welding. The experimental results showed that the proposed RLT-GMAW process had an excellent seam tracking performance and high welding deposition rate. Even if there were some electromagnetic interactions between the two arcs, the deviation of the welding seam could also be reflected by the fluctuation of the welding currents on the leading arc once the correct welding parameters were selected. Based on the detected deviation, the welding tracking experiments showed that the proposed self-turning fuzzy controller had a good performance for the RLT-GMAW process seam tracking.展开更多
智能化焊接在推进“工业强基”工程、支撑国家建设及国防安全中起到重要作用,从重大装备到精细结构,焊接都是不可或缺的关键技术,而机器人作为智能化焊接的重要载体,推动“以机器代替人,以机器解放人”的过程中将发挥重要作用.文中从焊...智能化焊接在推进“工业强基”工程、支撑国家建设及国防安全中起到重要作用,从重大装备到精细结构,焊接都是不可或缺的关键技术,而机器人作为智能化焊接的重要载体,推动“以机器代替人,以机器解放人”的过程中将发挥重要作用.文中从焊接制造全流程的场景建模、焊接过程形性原位感知、自适应调控、工艺知识构建等关键技术出发,重点阐述了焊接机器人的“免示教”编程环境感知、点云配准、焊缝轨迹规划和焊道自适应编排等共性技术的研究现状,以智能化焊接制造过程多源信息监测及控制系统为例,提出了基于IIOT-MAS(industrial internet of things-multi-agent system)焊接制造系统分层结构模型,介绍了焊接多模态信息感知、融合及工艺知识建模等共性科学问题,并介绍了工程机械部件焊接现场感知数据在线学习和模型-数据双驱动的焊接质量评价模型典型案例,探讨了机器人焊接智能化的发展趋势和所面临的挑战.展开更多
基金supported by the National Natural Science Foundation of China(Grant No.51465043)
文摘Tandem gas metal arc welding （ T-GMAW） process shows a high deposition rate that up to three times o f the single electrode GMAW, so the welding speed could be significantly increased in this process. However, the majority o f this process applications are based on the pre-programmed robotic welding, which does not allow them to track the seam real-time during welding. Rotating arc sensor, sensing the seam position by detecting the changing of welding currents, has been widely adopted in the automatic robot welding process. It is proposed in this paper to integrate the rotating arc sensor with a trailing torch to develop a new approach of rotating arc lead tandem gas metal arc welding （RLT-GMAW） process. The characteristics of the welding currents in the proposed new welding process were firstly studied, and then a self-turning fuzzy control seam tracking strategy was developed for the mobile robot automatic welding. The experimental results showed that the proposed RLT-GMAW process had an excellent seam tracking performance and high welding deposition rate. Even if there were some electromagnetic interactions between the two arcs, the deviation of the welding seam could also be reflected by the fluctuation of the welding currents on the leading arc once the correct welding parameters were selected. Based on the detected deviation, the welding tracking experiments showed that the proposed self-turning fuzzy controller had a good performance for the RLT-GMAW process seam tracking.
文摘智能化焊接在推进“工业强基”工程、支撑国家建设及国防安全中起到重要作用,从重大装备到精细结构,焊接都是不可或缺的关键技术,而机器人作为智能化焊接的重要载体,推动“以机器代替人,以机器解放人”的过程中将发挥重要作用.文中从焊接制造全流程的场景建模、焊接过程形性原位感知、自适应调控、工艺知识构建等关键技术出发,重点阐述了焊接机器人的“免示教”编程环境感知、点云配准、焊缝轨迹规划和焊道自适应编排等共性技术的研究现状,以智能化焊接制造过程多源信息监测及控制系统为例,提出了基于IIOT-MAS(industrial internet of things-multi-agent system)焊接制造系统分层结构模型,介绍了焊接多模态信息感知、融合及工艺知识建模等共性科学问题,并介绍了工程机械部件焊接现场感知数据在线学习和模型-数据双驱动的焊接质量评价模型典型案例,探讨了机器人焊接智能化的发展趋势和所面临的挑战.
