Neural network control of spot welding

Details Neural network control of spot welding Neural network control of spot welding

1997-09-17

2000-01-25

Hafiz, Tariq R.

Data processing: artificial intelligence

Neural network

Learning task

706 20, 706 23, 219110, 2191171, 21912164, 21913001, G06E 100, G06E 300, G06F 1518, G06G 700

Patent

active

060187298

ABSTRACT:
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.

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Messler, R.W., et al., An Intelligent Control System for Resistance Spot Welding Using aNeural Network and Fuzzy Logic, Industry Applications Conference, 1995. Thirteenth IAS Annual Meeting, IAS '95., Conference record of the 1995 IEEE Volume: 2 page(s): Jan. 1995.

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