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Embedded processing methods for online visual analysis of laser welding

机译:嵌入式加工方法,用于激光焊接的在线视觉分析

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Online monitoring and closed-loop control of laser welding offer great possibilities for achieving better weld quality. Earlier work on visual laser welding monitoring has mainly focused on aluminum and fairly thin steel used, for example, in car production. We extend this work by focusing on the automated analysis of the phenomena present in the laser welding of thick steel, where all of the phenomena related to the weld quality are still not well understood or controlled. This paper presents the implementation, test results and analysis for weld monitoring methods implemented on a compact smart camera system. The applied embedded sensor-processor platform allows for high-speed implementation of image capture and dynamic range compression, real-time seam tracking and spatter feature extraction. The paper describes experimental results from implemented real-time algorithms for seam tracking and spatter extraction and additional off-line analysis of methods for spatter tracking and seam widening detection, which are also feasible for future online hardware implementation. The results suggest that it is possible to integrate a compact laser welding analysis system, which achieves analysis rates that are sufficient for real-time process control.
机译:激光焊接的在线监控和闭环控制为实现更好的焊接质量提供了极大的可能性。早期的视觉激光焊接监测的工作主要集中在铝和相当薄的钢上,例如在汽车生产中使用。我们通过专注于厚钢激光焊接中存在的现象的自动分析来扩展这项工作,其中所有与焊接质量相关的现象仍然不受欢迎或控制。本文介绍了在紧凑型智能摄像机系统上实现的焊接监控方法的实施,测试结果和分析。应用的嵌入式传感器处理器平台允许高速实现图像捕获和动态范围压缩,实时缝线跟踪和喷溅功能提取。本文介绍了用于接缝跟踪和飞溅的实时算法的实验结果,以及用于飞溅跟踪和接缝扩展检测方法的额外离线分析,这对于未来的在线硬件实现也是可行的。结果表明,可以集成一个紧凑的激光焊接分析系统,该系统实现了足以进行实时过程控制的分析速率。

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