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A study on the estimate of weld bead shape and the compensation of welding parameters by considering weld defects in horizontal fillet welding

机译:考虑水平角焊缝焊接缺陷的焊缝形状估计和焊接参数补偿研究

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Generally, though we use a vision sensor or arc sensor in the welding process, it is difficult to define the welding parameters which can be applied to weld quality control. The important parameters in arc welding are arc voltage, welding current, welding speed and they affect the weld bead shape, the stability of the welding process and weld quality. Therefore, it is difficult to determine the unique relationship between the weld bead geometry and the combination of various welding conditions. Due to the various difficulties, we intend to use fuzzy logic and neural networks to solve these problems. Therefore, the combination of fuzzy logic and neural networks has an effect on removing the weld defects, improving the weld quality and finding the desired weld bead shape. Finally, this system can help us make an estimate of the weld bead shape and remove the weld defects.
机译:通常,尽管我们在焊接过程中使用视觉传感器或电弧传感器,但是很难定义可用于焊接质量控制的焊接参数。电弧焊的重要参数是电弧电压,焊接电流,焊接速度,它们会影响焊缝形状,焊接过程的稳定性和焊接质量。因此,难以确定焊缝几何形状与各种焊接条件的组合之间的唯一关系。由于种种困难,我们打算使用模糊逻辑和神经网络来解决这些问题。因此,模糊逻辑和神经网络的结合对消除焊接缺陷,提高焊接质量和找到所需的焊缝形状具有影响。最后,该系统可以帮助我们估算焊缝形状并消除焊缝缺陷。

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