NEURAL NETWORK CONTROL OF SPOT WELDING

A spot welder comprises a neural network for processing, in real time, current and voltage energizing a weld in progress. The neural network generates a predicted time of optimal weld strength and/or nugget size for the weld in progress. A controller terminates the weld in progress at the predicted time. A method for controlling a spot welder comprises the steps of: sensing in real time current and voltage energizing a spot weld in progress; predicting a time of optimal weld strength and/or nugget size with a neural network responsive to the sensed current and voltage; and, terminating the weld in progress at the predicted time. A sensor for electromotive forces (EMF) induced by the spot welder can generate a signal for canceling out a large fraction of EMF components in at least one or both of the current and voltage signals. EMF components are substantially precluded in the current signal if the current sensor uses a buried shunt. Termination of the weld in progress at the predicted time is prevented when the predicted time precedes a predetermined minimum weld duration. The weld in progress is terminated at a predetermined maximum weld duration when the predicted time is after the predetermined maximum weld duration.