The joints of RSW for HSHSS were prepared with IF spot weld equipment. The weld nugget, fracture mode, microstructure and micro-hardness of the joints were investigated. The weld nugget increases and the fracture mode changes from interfacial fracture to nugget plug fracture with the increasing welding current. There are three distinct zones in the weld joint: weld nugget, heat affected zone (HAZ) and base metal. The microstructure of HAZ includes tempered zone (HAZ-1), incomplete quenching zone (HAZ-2) and complete quenching zone (HAZ-3). The micro-hardness of weld nugget and HAZ-3 is same with the base metal. The micro-hardness of HAZ-1 and HAZ-2 is smaller than that of base metal.
The ultra-high strength quenched 22MnB5 steel is researched in this paper, the intermediate frequency inverter & electric servo welding gun system is used to weld the sheets, experiments included of tensile-shear with synchronous electrical testing, microstructure of the material and fractures analysis and the Vickers-Hardness testing. The results point out that the maximum hardness is located at weld nugget, and the minimum hardness is appeared in heat affected zone (HAZ). Fracture is formed under the combined effects of shear stress and normal stress, the shear stress contributes to interfacial fracture, and leads to rupture. Non-uniformity of the microstructure caused by spot welding, changed the property of the material in nugget, stress-strain relationship of this area is nonlinear. The results also show that the conventional weld size guidance of 4√t is not sufficient to produce nugget pullout failure mode for 22MnB5 UHSS spot welds.
The active droplet oscillation is a method previously proposed to detach the droplet at currents below the transition current. In this method, a droplet oscillation is actively excited when the current is switched from the exciting peak level to base level. The downward momentum of the droplet is utilized to enhance the droplet detachment. In this work, the current waveform is modified to achieve stronger droplet oscillation with lower average current. The critical change is to separate the droplet growing and exciting processes such that the two processes can be controlled independently. The heat input can thus be reduced, and stronger droplet oscillation is obtained. A further optimized current waveform is proposed to maximize the droplet oscillation energy despite the growing current level.
Skilled welders can estimate and control the weld penetration based on weld pool observation. This implies that an advanced control system could be developed to control the penetration by emulating the decision making process of the human welder. In this paper a nonlinear dynamic model is established to correlate the process inputs (welding current and traveling speed) and weld penetration in Gas Tungsten Arc Welding (GTAW). An innovative 3D vision sensing system capable of measuring the weld pool characteristic parameters in real-time is utilized. Dynamic experiments are conducted under various welding conditions. Dynamic linear model is first constructed and the results are analyzed. The linear model is then improved by incorporating a nonlinear operating point modeled by Adaptive Neuro Fuzzy Inference System (ANFIS). It is found that the penetration state can be better modeled by the proposed ANFIS model.
Controlled metal transfer in gas metal arc welding (GMAW) and its modifications including the double-electrode GMAW implies controllable heat and mass inputs and better assured weld quality. To understand, analyze, and control the metal transfer process, the droplet should be monitored in real time. Due to the fast development and transfer of the droplet, the monitoring speed is a key. A tracking method that takes advantage of results from previous images to speed the processing is advantageous. In this paper, Kalman Filter tracking and Least Square Match tracking algorithms are developed to track a droplet in the innovative double-electrode GMAW after its original position is identified. Experimental results showed that the Kalman Filtering algorithm is not suitable for this application due to the limited life span of each droplet. Instead, the Least Square Match algorithm is effective in tracking a droplet if a universal droplet template can be found and defined. However, there are no universal templates suitable for all the droplets. Hence, a real time template updating and LSM tracking method is proposed to track the droplet effectively. Experimental results verified its tracking accuracy.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.