Controlling of torch attitude and seam tracking using neuro arc sensor

It is important to realize intelligent welding robots to obtain a good quality of weld. For this purpose, it is required to detect the deviation from the center of the groove, the torch height, and the torch attitude. In order to simultaneously detect these, the authors propose a neuro arc sensor as the sensor fusion by using a neural network. First, the authors deal with the welding phenomena as the melting phenomena in the electrode wire of the MIG welding. Next, the training data of the neural networks are made from the numerical simulations. A neuro arc sensor is trained so as to get the desired performance by the backpropagation method. The welding experiments are carried out to examine the performance of the neuro arc sensor. A good performance of the neuro arc sensor is obtained. By using it, the seam tracking can be performed in the T-joint welding.