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Online measurement of weld fusion state using weld pool image and neurofuzzy model

机译:使用焊接池图像和神经燃料模型在线测量焊接融合状态

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Proper fusion is crucial in generating a sound weld. Successful control of the fusion state requires accurate measurements of both the top-side and back-side bead widths. A top-side sensor based system is preferred so the sensor can be attached to and move with the torch. Thus, the system must be capable of estimating the back-side bead width using top-side parameters. Because skilled human operators can estimate the fusion state through observation of the weld pool, in this work a neurofuzzy system is developed to infer the back-side bead width from the pool geometry. It is found that the back-side bead width can be estimated with high accuracy by the identified neurofuzzy model. Thus, accurate feedback of the fusion state can be provided for controlling the fusion state.
机译:适当的融合在产生声音焊接时至关重要。融合状态的成功控制需要精确测量顶侧和背面珠宽度。基于顶侧的基于传感器的系统是优选的,因此传感器可以附接到并与焊炬一起移动。因此,系统必须能够使用顶侧参数估计后侧珠宽。由于熟练的人类操作员可以通过观察焊接池来估计融合状态,因此在这项工作中,开发了一种神经繁茂的系统,以从池几何形状推断后侧珠子宽度。发现可以通过所识别的神经摩擦模型以高精度估计后侧珠宽度。因此,可以提供用于控制融合状态的融合状态的精确反馈。

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