Online estimation and characteristic analysis of double nugget diameters during aluminum/steel resistance spot welding process

Online estimation of the double nugget diameters was performed by means of a back propagation neural network. The double nugget diameters were obtained using actual welding experiment and numerical simulation, according to different characteristics of aluminum nugget and steel nugget. The input of the neural network was some key characteristic parameters extracted from dynamic power signal, which were peak point, knee point and their variation rate over time, as well as heat energy delivered into the welding system. The architecture of the neural network was confirmed by confirming the number of neurons in hidden layer through a series of calculations. The key parameters of the neural network were obtained by means of training 81 arrays of data set. Then, the neural network was used to test the remaining 20 arrays of verifying data set, and the results showed that both of the mean errors for the two nugget diameters were below 3%. In addition, corresponding analyses showed that the accuracy of two nugget diameters was higher than that of tensile-shear strength.