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Image processing method for automatic tracking of the weld line in plasma robotic welding

机译:等离子机器人焊接中焊接线自动跟踪的图像处理方法

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摘要

For automatic control in plasma welding (PAW), the welding situation must sometimes be observed in real-time. However, the welding quality of PAW depends on the performance of the tracking result. Therefore, to determine gaps in the welding, we developed an image processing method that automatically tracks the weld line. Since the plasma electrode is buried in the torch, visual judgment by the human eye is difficult. This method replaces human sight with a visible automatic profile control that exactly teaches the plasma torch during the welding process. The image processing method for automatic tracking adopts a hybrid optimization process with template matching, which identifies small parts of a welding characteristic image that match the template image. In general, template matching provides a partial quality control. In special cases, the welding gap and its boundary are effectively detected by a boundary detection method, and variable gaps detected in the real-time tracking are analyzed to ensure high-welding quality. In verification trials, our method demonstrated efficient welding work and effectively reduced the false torch guidance.
机译:对于等离子体焊接(爪子)的自动控制,有时必须实时观察焊接情况。但是,爪子的焊接质量取决于跟踪结果的性能。因此,为了确定焊接中的间隙,我们开发了一种自动跟踪焊接线的图像处理方法。由于等离子体电极被埋在焊炬中,因此人眼的视觉判断难。该方法用可见的自动轮廓控制取代人的视线,该控制在焊接过程中精确地教导等离子体炬。用于自动跟踪的图像处理方法采用具有模板匹配的混合优化过程,其识别匹配模板图像的焊接特性图像的小部分。通常,模板匹配提供了部分质量控制。在特殊情况下,通过边界检测方法有效地检测焊隙及其边界,分析了在实时跟踪中检测的可变间隙以确保高焊接质量。在验证试验中,我们的方法证明了有效的焊接工作,有效地降低了假火炬指导。

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