Noise Rejection for Joint Configuration Detection of Arc Welding by Using Neural Network(Physics, Process, Instrument & Measurements)

概要

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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.
大阪大学の論文