Assessing Electrode Characteristics in Continuous Resistance Spot Welding of BH 340 Steel Based on Dynamic Resistance

The aim of this investigation is to offer a data-based scheme for predicting electrode wear in resistance spot welding. One of the major factors affecting the mechanical properties of spot welds and the variation in weld quality is electrode wear and alloying. In this study, Rogowski coils and twisted pairs attached to the top and bottom electrodes were used to obtain the welding current and the voltage between the electrodes in the welding process, thereby calculating the dynamic resistance value during the welding process. The electrode tip diameter was obtained from the pressure exerted by the upper and lower electrodes on the carbon paper when the current was cut off and was regarded as an indicator of electrode wear. By continuously welding 0.5 mm thick BH 340 steel plates until the electrode failed, the dynamic resistance signal was recorded in real time. Simultaneously, the electrode diameter after every several welds was also recorded. On this basis, the correlation between electrode tip diameter and dynamic resistance is studied. In order to quantitatively study the mapping relationship between dynamic resistance and electrode wear, 10 characteristic values were extracted from the dynamic resistance, and the stepwise regression method was used to obtain the regression formula between the characteristic values and the electrode tip diameter. Using new data to verify the effectiveness of the regression model, the acquired results display that the maximum error between the predicted value of the electrode tip diameter and the measured value obtained by the regression equation with the interactive quadratic term is 0.3 mm, and the corresponding relative error is 7.69%. When welding with a new pair of electrodes, the maximum absolute error was 0.72 mm, and the relative error of the model prediction is within 20% according to the linear regression model with interaction terms. This indicates that this regression model is barely satisfactory for monitoring electrode condition.