저항 점용접 품질의 실시간 모니터링 및 제어를 위한 시스템 = Real Time Monitoring and Control System for Spot Weld Quality Assurance

다국어 초록 (Multilingual Abstract)

Resistance spot welding has been widely used in the sheet metal joining processes because of its high productivity and convenience. In the resistance spot welding process, the size of molten nugget and tensile-shear strength are criterion to assess weld quality. However real-time monitoring of the nugget size and tensile-shear strength is a extremely difficult problem. This paper describes the design of an artificial neural networks(ANN) estimator to predict the nugget size for on-line use of weld quality monitoring. The main task of the ANN estimator is to realize the mapping characteristics from the sampled dynamic resistance signal to the actual nugget size and tensile-shear strength through training. The results are quite promising in that real-time estimation of the invisible nugget size and tensile-shear strength can be achieved by analyzing the welding process variables without any conventional destructive testing of welds.