AUTOMATED ROTOR WELDING PROCESSES USING NEURAL NETWORKS `

Methods and apparatus for monitoring an arc welding process are disclosed. In a preferred embodiment, the present invention creates a digital representation of the arc created during welding and, using a neural network computer, determines if the arc is representative of normal or abnormal welding conditions. The neural network disclosed is trained to identify abnormal conditions and normal conditions and may be adaptively retrained to classify images that are not in the initial set of normal and abnormal images. In certain embodiments, other data, such as current, weld wire emission spectra, or shielding gas flow rate are also collected and the neural network is trained to monitor these data. Also, in certain embodiments, an audio signal is collected from the vicinity of the welding process and is used by the neural network computer to further classify the arc as normal or abnormal. The present invention is most preferably implemented in repetitive and continuous welding operations, such as those encountered in the manufacture and rebuilding of steam turbines.