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Noise Rejection for Joint Configuration Detection of Arc Welding by Using Neural Network

机译:神经网络的电弧焊联合形态检测中的噪声抑制

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On using the signal processing ability of Backpropagation Model of Neural Network, the noise rejection is performed on the image of a joint part of arc welding. The object image, which is obtained by the slit light slice method, is often used for the detection of joint configuration on the purpose of welding automation. The noise caused by the welding arc is superimposed on the image and disturbs the detection. Such noise is rejected through the learning process of Neural Network which is carried out for the noise imposed input images and the noiseless teacher images. The structure of the network, the image input method, the selection of the teacher image and the method to recover the resolution of the processed result are investigated experimentally. It is shown that the noise rejection is successfully done as the results.
机译:利用神经网络的反向传播模型的信号处理能力,对电弧焊接接头部分的图像进行噪声抑制。通过缝隙光切片法获得的目标图像通常用于焊接自动化的目的,以检测接头的形状。由焊接电弧引起的噪声会叠加在图像上,并干扰检测。这种噪声通过神经网络的学习过程被拒绝,该学习过程是针对施加噪声的输入图像和无噪声的教师图像执行的。实验研究了网络的结构,图像输入法,教师图像的选择以及恢复处理结果分辨率的方法。结果表明,噪声抑制已成功完成。

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