In order to explore the influence of welding parameters and to investigate the Al alloy (AA) nugget formation process, a comprehensive model involving electrical-thermal-mechanical and metallurgical analysis was established to numerically display the resistance spot welding (RSW) process within multiple fields and understand the AA-RSW physics. A multi-disciplinary finite element method (FEM) framework and a empirical sub-model were built to analyze the affecting factors on weld nugget and the underlying nature of welding physics with dynamic simulation procedure. Specifically, a counter-intuitive phenomenon of the resistance time-variation caused by the transient inverse virtual variation (TIVV) effect was highlighted and analyzed on the basis of welding current and temperature distribution simulation. The empirical model describing the TIVV phenomenon was used for modifying the dynamic resistance simulation during the AA spot welding process. The numerical and experimental results show that the proposed multi-field FEM model agrees with the measured AA welding feature, and the modified dynamic resistance model captures the physics of nugget growth and the electrical-thermal behavior under varying welding current and fluctuating heat input.
To classify the quality of the resistance spot welding process, a relationship between the welder electrode displacement curve characteristics and the weld shear force has been explored. Eleven statistical features of the displacement signMs are extracted to represent the welding quality. Self-organizing map （SOM） neural networks have been employed to discover their quantitative relationship. In order to identify the influence of various displacement curve features, all of the available combinations have been used as inputs for SOM neural networks. Further we analyze the impact of each feature on the classification results, yielding the best quality-indicative combination of characteristics. There is no determinant relationship between the welding quality and the level of expulsion rate. The quality of welding is most impacted by the maximum electrode displacement, the span of welding process and the centroid of the electrode displacement curve. The experiments show that SOM is feasible to assess the welding quality and can render the visualized intuitive evaluation results.
