다층 신경회로망을 이용한 GMA 용접 공정에서의 용융지 크기의 예측

Estimation of weld pool sizes in GMA welding processes using a multi-layer neural net

This paper describes the design of a neural network estimator to estimate weld pool sizes for on-line use of quality monitoring and control in GMA welding processes. The estimator utilizes surface temperatures measured at various points on the top surface of the weldment as its input. The main task of the neural net is to realize the mapping characteristics from the point temperatures to the weld pool sizes through training, A series of bead-on plate welding experiments were performed to assess the performance of the neural estimator.