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To achieve high quality resistance spot welds (RSW) through intelligent manufacturing of automotive body structures, adaptive control for RSW processes becomes imperative and has gained global attention. Tracking ideal process signal profiles predetermined offline is a commonly-used strategy to realize the adaptive control of RSW and is found effective in compensating for the adverse impacts caused by shunting and electrode wear. However, the validity of this control strategy under other types of disturbance is still unproven. In this article, typical abnormal welding conditions, i.e. initial sheet gaps and edge proximity, were designed to test the performance of output tracking control strategies for steel RSW. Two types of process signals including dynamic resistance and electrode displacement were tracked to approach the referenced signal profiles through the adjustment of weld parameters. Comparative studies were conducted based on metallographic analysis and mechanical tests to validate the two tracking control strategies. Results demonstrated that gap and edge proximity conditions decreased the nugget diameter and the tensile-shear strength of the welds. When satisfactory tracking of the reference resistance signal was realized under these two types of abnormal conditions, weld properties are further degraded, owing to a reduction in welding current. On the contrary, tracking the electrode displacement signal mitigated the negative influences from the disturbance through increasing welding current properly. When the disturbance was too severe, the displacement-based strategy raised the risk of expulsion. The findings suggest that tracking the dynamic resistance signal is not optimal for adaptive control of steel RSW, while tracking the electrode displacement signal is more effective. However, to achieve a more satisfactory adaptive control result, the output tracking control should be used in combination with expulsion suppression techniques.

Resistance spot welding (RSW) is the predominate joining method used for steel auto body assembly. Significant effort has been made to control and inspect the RSW quality in real time to guarantee the security and the reliability of body structure joints. Among the various methods, monitoring of the surface indentation is proven to be a promising method to actualize online weld quality assessment. In this article, a new approach to online measurement of indentation depth for the RSW process using a servo gun is proposed. The approach entails the development of a modified measurement system to eliminate the transmission error of the toothed belt drive and compensate the deflection of the fixed electrode arm, which enables precision measurement of the electrode tip displacement (ETD). Furthermore, consideration is given to explaining the downtrend of the displacement curve during the hold time within the RSW process, and the indentation depth at ambient temperature is finally estimated through curve fitting and experimental correction. The experimental results show that the error of indentation estimation could be limited to $\pm 30~\mu \text{m}$ ( $\pm 2\sigma$ ) at 95% confidence level, which far surpasses the performance of the previous method. Based upon sensitivity analysis, the precision is proven to be robust to different workpieces ranging from low-carbon steel to high-strength steel.

Weld expulsion is a universal problem during resistance spot welding (RSW) process and has potential damage to welding products and surrounding facilities. This study presents a new approach to the online evaluation of expulsion intensity using the amount of molten metal ejected during the expulsion. Through the newly developed multi-sensor monitoring and high-speed camera system, instantaneous features of process signals involving dynamic resistance, electrode force, and electrode displacement are simultaneously monitored and comparatively studied. The experimental results show that the amount of sudden decrease in the force and displacement signals is proportional to the weight of the expelled metal, but no apparent relationship is observed between the sudden resistance drop and the expulsion severity. Based upon further analysis, the abrupt change of electrode force is proven an optimal feature to precisely assess the magnitude of expulsion for a servo gun system. After calibration, the error of expulsion estimation could be limited to ±16.8 mg (±2σ) at a 95% confidence level, and the accuracy is robust to varying workpieces ranging from low carbon steel to high strength steel. This study may pave the way to online control the expulsion to the minimum level.

Welding expulsion is a common problem in the resistance spot welding (RSW) process, which severely impacts weld quality and surrounding facilities. Existing expulsion control strategies are ineffective for complex and changeable welding conditions. This article studied the growth relationship between weld nugget and corona bond under two abnormal conditions: edge proximity (EP) and initial sheet gaps (IG). It is testified that expulsion would occur when the nugget size exceeds the corona bond size under EP and IG conditions. Reducing the welding current before the expulsion time can increase the size difference between the corona bond and the weld nugget, thereby delay and even eliminate the occurrence of expulsion. In this way, a novel online expulsion control strategy, named short-time current regulation (STCR), is proposed through the expulsion moment analysis of historical weld data. The effect of the new control strategy is verified with workpieces ranging from low carbon steel to ultra-high strength steel. Experimental results showed that STCR can effectively reduce the amount of expelled metal, decrease the indentation depth, and increase the nugget diameter. The method not only works well under one specific abnormal condition but also adapts to the transition between different welding conditions. This novel expulsion control strategy can help achieve the expulsion-free RSW process in mass production without frequent manual offline optimization of welding parameters.

Weld expulsion is one of the most common welding defects during the 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 correlation 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.