Analytical kinematics and working-condition simulation for friction stir welding (FSW) robot

Luo, Haitao; Wang, Zhihui; Fu, Jia; Chen, Zhengcang; Leng, Yuquan

doi:10.1109/icinfa.2015.7279615

Cited by 4 publications

(3 citation statements)

References 5 publications

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“…Traditional FSW equipment is generally developed using CNC machines [3]. While it offers high accuracy and strong structural stiffness, its limited workspace restricts the welding of complex workpieces [4]. Industrial robots, with their strong versatility, large working space, and low development costs, have already been widely applied in the welding field [5].…”

Section: Introductionmentioning

confidence: 99%

Optimization of Installation Position for Complex Space Curve Weldments in Robotic Friction Stir Welding Based on Dynamic Dual Particle Swarm Optimization

Zong,

Kang,

Chen

et al. 2024

Processes

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Robotic friction stir welding (RFSW), with its wide application range, ample working space, and task flexibility, has emerged as a vital development in friction stir welding (FSW) technology. However, the low stiffness of serial industrial robots can lead to end-effector deviations and vibrations during FSW tasks, adversely affecting the weld quality. This paper proposes a dynamic dual particle swarm optimization (DDPSO) algorithm through a new comprehensive stability index that considers both the stiffness and vibration stability of the robot to optimize the installation position of complex space curve weldments, thereby enhancing the robot’s stability during the FSW process. The algorithm employs two independent particle swarms for exploration and exploitation tasks and dynamically adjusts task allocation and particle numbers based on current results to fully utilize computational resources and enhance search efficiency. Compared to the standard particle swarm optimization (PSO) algorithm, the DDPSO approach demonstrated superior search capabilities and stability of optimization results. The maximum fitness value improved by 4.2%, the average value increased by 12.74%, and the concentration level of optimization results rose by 72.91% on average. The new optimization method pioneers fresh perspectives for optimizing the stability of RFSW, providing significant grounds for the process optimization and offline programming of complex spatial curve weldments.

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Section: Introductionmentioning

confidence: 99%

Optimization of Installation Position for Complex Space Curve Weldments in Robotic Friction Stir Welding Based on Dynamic Dual Particle Swarm Optimization

Zong,

Kang,

Chen

et al. 2024

Processes

View full text Add to dashboard Cite

show abstract

“…At present, FSW equipment is mainly developed based on NC machines, and it is difficult to achieve complex welding work [9]. To enhance the performance of FSW equipment and expand its application fields, a 5-DOF gantry robot with a slide rail and rotary table was developed for FSW [10].…”

Section: Introductionmentioning

confidence: 99%

Digital Twin Virtual Welding Approach of Robotic Friction Stir Welding Based on Co-Simulation of FEA Model and Robotic Model

Chen,

Zong,

Kang

et al. 2024

Sensors

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Robotic friction stir welding has become an important research direction in friction stir welding technology. However, the low stiffness of serial industrial robots leads to substantial, difficult-to-measure end-effector deviations under the welding forces during the friction stir welding process, impacting the welding quality. To more effectively measure the deviations in the end-effector, this study introduces a digital twin model based on the five-dimensional digital twin theory. The model obtains the current data of the robot and six-axis force sensor and calculates the real-time end deviations using the robot model. Based on this, a virtual welding model was realized by integrating the FEA model with the digital twin model using a co-simulation approach. This model achieves pre-process simulation by iteratively cycling through the simulated force from the FEA model and the end displacement from the robot model. The virtual welding model effectively predicts the welding outcomes with a mere 6.9% error in lateral deviation compared to actual welding, demonstrating its potential in optimizing welding parameters and enhancing accuracy and quality. Employing digital twin models to monitor, simulate, and optimize the welding process can reduce risks, save costs, and improve efficiency, providing new perspectives for optimizing robotic friction stir welding processes.

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“…However, excessive eccentric errors can increase fluctuations in welding forces, degrade weld quality, and lead to more welding defects [ 21 , 22 ]. Traditional FSW equipment, which has higher stiffness, is less affected by changes in welding forces [ 23 ]. In contrast, the lower stiffness at the robot end-effector in FSW robots leads to forced vibrations under the influence of welding forces, thereby affecting the welding process and the quality of the welds.…”

Section: Introductionmentioning

confidence: 99%

Active Vibration Avoidance Method for Variable Speed Welding in Robotic Friction Stir Welding Based on Constant Heat Input

Zong,

Kang,

Chen

2024

Materials

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Robotic Friction Stir Welding (RFSW) technology integrates the advantages of friction stir welding and industrial robots, finding extensive applications and research in aerospace, shipbuilding, and new energy vehicles. However, the high-speed rotational process of friction stir welding combined with the low stiffness characteristics of serial industrial robots inevitably introduces vibrations during the welding process. This paper investigates the vibration patterns and impacts during the RFSW process and proposes an active vibration avoidance control method for variable speed welding based on constant heat input. This method utilizes a vibration feedback strategy that adjusts the spindle speed actively if the end-effector’s vibration exceeds a threshold, thereby avoiding the modal frequencies of the robot at its current pose. Concurrently, it calculates and adjusts the welding speed of the robot according to the thermal equilibrium equation to maintain constant heat input. A simplified dynamic model of the RFSW robot was established, and the feasibility of this method was validated through simulation experiments. This study fills the gap in vibration analysis of RFSW and provides new insights into control strategies and process optimization for robotic friction stir welding.

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Analytical kinematics and working-condition simulation for friction stir welding (FSW) robot

Cited by 4 publications

References 5 publications

Optimization of Installation Position for Complex Space Curve Weldments in Robotic Friction Stir Welding Based on Dynamic Dual Particle Swarm Optimization

Optimization of Installation Position for Complex Space Curve Weldments in Robotic Friction Stir Welding Based on Dynamic Dual Particle Swarm Optimization

Digital Twin Virtual Welding Approach of Robotic Friction Stir Welding Based on Co-Simulation of FEA Model and Robotic Model

Active Vibration Avoidance Method for Variable Speed Welding in Robotic Friction Stir Welding Based on Constant Heat Input

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