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In this study, taking six-series aluminium alloy and DC06 galvanised steel resistance spot welding as the object of study, the impacts of the electrode cap shape and process parameters on the joint welding performance were analysed, and the electrode cap was optimised. The optimised process parameters involved the use of spherical asymmetric electrodes and a pre-welding preheating step for zinc extrusion treatment, followed by a double pulse for welding. The optimal parameters resulted in an aluminium/steel spot welding head average pull shear failure load of 2858.7 N and aluminium/aluminium spot welding head failure force of 2436 N, reaching 117.3% of its original value. The minimum force value (2253.4 N) was greater than 92.5%, and the failure section was all from the aluminium side in parent material button failure, achieving good final results. [ABSTRACT FROM AUTHOR]

The impact of emotions on health, especially stress, is receiving increasing attention. It is important to provide a non-invasive affect detection system that can be continuously monitored for a long period of time. Multi-sensor fusion strategies can better improve the performance of affect detection models, but there are also problems such as insufficient feature extraction and poor spatiotemporal feature fusion. Therefore, this study proposes a feature-level fusion method based on long short-term memory and one-dimensional convolutional neural network to extract temporal and spatial features of electrocardiogram, electromyogram, electrical activity, temperature, accelerator and response data, respectively, and then fuse them in a summation fashion for affect and stress detection. In particular, we added the tanh activation function before feature fusion, which can improve the model's performance. We used the wearable affect and stress detection dataset to train the model, which includes three different emotion states (neutral, stress, and amusement) for three-class emotion classification with accuracy and F1-scores of 87.82% and 86.68%, respectively. Due to the importance of stress, we also studied binary classification for stress detection, where neutral and amusement were combined as non-stress, with accuracy and F1-scores of 94.9% and 94.98%, respectively. The performance of the proposed model outperforms other control models and can effectively improve the performance of affect and stress detection, and promote medical care, health care and elderly care. [ABSTRACT FROM AUTHOR]

This article studies the multi-layer and multi-pass welding of the circumferential weld in the thick pipe welding of an aviation enterprise, based on the static characteristics of the welding arc, through data calculations and experiments to verify the relationship between arc voltage and arc length, proposes to use the arc voltage controller to accurately adjust the arc voltage in real time, improve the welding stability, use the welding torch wiggler to expand the welding fusion width, meet the adaptive adjustment of the wide weld, and build the main control system based on programmable logic controller (PLC) control. Integrating all subsystems and put them into the actual production of the enterprise, significantly improves the production efficiency of parts welding, reduces welding defects, and improves the quality of aviation parts. [ABSTRACT FROM AUTHOR]