Artificial neural networks applied to arc welding process modeling and control

The authors explain some basic concepts relating to neural networks and discuss how they can be used to model weld bead geometry in terms of the parameters of the equipment selected to produce the weld. Approaches to utilization of neural networks in process control are discussed as well. The need for modeling transient as well as static characteristics of physical systems for closed-loop control is pointed out, and an approach for achieving this is presented. The performance of neural networks for modeling is presented and evaluated using actual welding data. It is concluded that the accuracy of neural network modeling is fully comparable to the accuracy achieved by more traditional modeling schemes.<>