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Resistance spot welding (RSW) is widely used in auto-body manufacturing, and the weld quality is critical to ensure the safety and reliability of an automobile structure. The dynamic resistance (DR) signal is one of the most frequently applied process signals for real-time quality monitoring and control of RSW. However, the accuracy of DR measurement is highly affected by the inductive component of the secondary voltage signal. In a mediumfrequency direct-current (MFDC) RSW system, it is proven that traditional DR measurement methods such as the root mean square (RMS) method and average method fail to eliminate the interference of inductance, and barely meet the monitoring requirements. Therefore, a novel real-time DR measurement method based on a forgetting-factor recursive least square algorithm is proposed and tested under simulated and experimental conditions in this paper. Sensitivity analysis is performed to optimize the forgetting factor, which is proven to be the critical parameter of the novel method to balance the convergence speed and oscillation amplitude. With the optimized forgetting factor, the error analysis and comparative study are conducted under different welding modes. The results show that the inductive noise can be effectively eliminated by the new method. The measurement error of the proposed method is limited within ±6 µΩ at a 99.73% confidence level (±3σ) at both constant and time-varying current modes. This study can pave the way for real-time monitoring and control for an MFDC RSW system.

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In order to control and monitor the quality of middle frequency direct current (MFDC) resistance spot welding (RSW), precision measurement of the welding current up to 100 kA is required, for which Rogowski coils are the only viable current transducers at present. Thus, a highly accurate analogue integrator is the key to restoring the converted signals collected from the Rogowski coils. Previous studies emphasised that the integration drift is a major factor that influences the performance of analogue integrators, but capacitive leakage error also has a significant impact on the result, especially in long-time pulse integration. In this article, new methods of measuring and compensating capacitive leakage error are proposed to fabricate a precision analogue integrator system for MFDC RSW. A voltage holding test is carried out to measure the integration error caused by capacitive leakage, and an original integrator with a feedback adder is designed to compensate capacitive leakage error in real time. The experimental results and statistical analysis show that the new analogue integrator system could constrain both drift and capacitive leakage error, of which the effect is robust to different voltage levels of output signals. The total integration error is limited within ±0.09 mV s −1 0.005% s −1 or full scale at a 95% confidence level, which makes it possible to achieve the precision measurement of the welding current of MFDC RSW with Rogowski coils of 0.1% accuracy class.

Weld expulsion is one of the most common welding defects during resistance spot welding (RSW) process especially for high strength steels (HSS). In order to control and eventually eliminate weld expulsion in production, accurate assessment of the expulsion severity should be the first step and is urgently required. Among the existing methods, real-time monitoring of RSW-related process signals has become a promising approach to actualize the online evaluation of weld expulsion. However, the inherent correlation between the process signals and the expulsion intensity is still unclear. In this work, a commonly used process signal, namely the electrode displacement and its instantaneous behavior when expulsion occurs are systematically studied. Based upon experiments with various electrodes and workpieces, a nonlinear relation between the weight of expelled metal and the sudden displacement drop accompanied by the occurrence of weld expulsion is observed, which is mainly influenced by electrode tip geometry but not by material strength or sheet thickness. The intrinsic relationship between this specific signal feature and the magnitude of expulsion is further explored through geometrical analysis, and a modified analytical model for online expulsion evaluation is finally proposed. It is shown that the improved model could be applied to domed electrodes with different tip geometries and varying workpieces ranging from low carbon steel to HSS. The error of expulsion estimation could be limited within ±20.4 mg (±2σ) at a 95% confidence level. This study may contribute to the online control of weld expulsion to the minimum level.