Audio-visual modelling and control of GMA welding

GMA 焊接的视听建模和控制

• 批准号: 6468-2007
• 负责人: Huissoon, JanPaul
• 金额: $ 2.11万
• 依托单位: University of Waterloo
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2007
• 资助国家: 加拿大
• 起止时间: 2007-01-01 至 2008-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=366182
• 关键词: Audio; visual; modelling; control; GMA

This research program is in the area of experimental gas metal arc (GMA) welding process identification and control. The objective is to investigate the relationships between visual and acoustic signals that expert human welders can sense when welding, and the control actions they employ in response to these.The motivation for pursuing this research is that the current state-of-the-art in robotic GMA welding systems still rely on what is essentially open-loop control: parameter settings are preset to values that should result in a good quality weld for a given joint geometry under constant conditions. However, expert human welders continually make adjustments to the welding torch position and speed, as well as to the voltage and wire feed-rate, in response to what they see and hear while they are welding. This human feedback control system is learned through experience, and is very effective at producing high quality welds. However, arc welding is a tiring and hazardous job involving exposure to noxious fumes, heat and intense ultra violet radiation, and it would therefore be of great benefit to develop fully automated / robotic welding systems capable of providing comparable feedback control that human welders excel at.The expected significance of this research is a better understanding of how professional welders react to the acoustic and visual cues they receive while welding, and how this can be applied to the automatic control of the GMA welding process. The benefits to society include the potential for reduced human exposure to the hazardous arc welding environment, while retaining the need for skilled welding professionals to oversee and program the robotic welding operations.

该研究计划是在实验气体保护金属极电弧焊（GMA）焊接过程识别和控制领域。其目的是研究焊接时专家焊工可以感知的视觉和声音信号之间的关系，以及他们响应这些信号而采用的控制动作。进行这项研究的动机是，目前机器人GMA焊接系统的最新技术仍然依赖于本质上的开环控制：参数设置被预设为在恒定条件下对于给定的接头几何形状应该产生良好质量焊接的值。然而，专业的人类焊工响应于他们在焊接时所看到和听到的，不断地对焊炬位置和速度以及电压和送丝速率进行调整。这种人工反馈控制系统是通过经验学习的，并且在生产高质量焊接方面非常有效。然而，电弧焊接是一项累人且危险的工作，涉及暴露于有毒烟雾、热量和强烈的紫外线辐射，因此，开发全自动/机器人焊接系统能够提供类似的反馈控制，人类焊工擅长。这项研究的预期意义是更好地了解专业焊工如何反应，他们收到的声音和视觉提示，焊接，以及如何将其应用于GMA焊接过程的自动控制。对社会的好处包括减少人类暴露于危险弧焊环境的可能性，同时保留对熟练焊接专业人员的需求，以监督和编程机器人焊接操作。