A feedforward deflection compensation scheme coupled with an offline path planning for robotic friction stir welding

Kolegain, Komlan; Léonard, François; Zimmer-Chevret, Sandra; Attar, Amarilys Ben; Abba, Gabriel

doi:10.1016/j.ifacol.2018.08.405

Cited by 12 publications

(7 citation statements)

References 18 publications

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“…The working area of manipulators can be represented as a three-dimensional working area. Now the robots is a very effective way to manufacturing parts of aerospace constructions [13][14][15][16][17][18]. However, in addition to geometrical problem, can be solved and thermic, stresses, quality's problem [19][20][21][22][23][24].…”

Section: Overview Of Friction Stir Welding Equipmentmentioning

confidence: 99%

Mathematical Simulating of the Process of Friction Stir Welding for the Manufacture of Tank Bottoms in Aerospace Construction

2020

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In modern aerospace technology, one of the perspective ways of assembly parts of thin metal plates is friction stir welding. The advantage of this method is the higher strength of the welds of aluminum alloy joints, compared with the traditional MIG welding for the assembly of rockets and space constructions. However, the lack of friction stir welding is a necessity of formation of the system “machine –tool - part” significantly more effort, which is caused by the need to stir the material in the weld zone in a plastic state. Friction stir welding is used to connect the individual elements of tanks and bodies, in particular, panels, elements of the bottoms with each other. In this paper, is consider the typical design for rocket and space technology bottoms of large tanks. For industrial robot equipped with a special head for friction welding with mixing, a mathematical model of obtaining a spherical bottom from individual segments is proposed. The paper presents a mathematical model describing the geometry of a spherical bottom with a flap articulation and a working zone of an industrial robot, which allows defining constraints on process operation continuous seam welding for standard designs of bottoms and hulls of rocket and space technology. The dependences allowing determining the initial position of the robot relative to the bottom for performing friction stir welding of the continuous seam are proposed.

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Section: Overview Of Friction Stir Welding Equipmentmentioning

confidence: 99%

Mathematical Simulating of the Process of Friction Stir Welding for the Manufacture of Tank Bottoms in Aerospace Construction

2020

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“…To reduce the impact of robot end displacement, offline programming methods were used to pre-compensate for end errors in the RFSW process. Kolegain et al [10] proposed a Processes 2024, 12, 536 2 of 22 deflection model-based feedforward compensation technique and an offline path planning using Bézier curves to solve the position and orientation deviations of the robot end effector during welding. Bai et al [3] presented a method for predicting and compensating for the end displacement of FSW robots to solve the problem of insufficient plunge depth.…”

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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“…However, the online detection and error compensation often exhibit latency and are less effective when performing highspeed or complex curve welding. To advance compensate for the end-effector deviation in the robot, a deflection model-based feedforward compensation technique and an offline path planning using Bézier curves were proposed to solve the position and orientation deviations in the robot end-effector during welding [16]. Well, most such studies assume that the stirring tool is subjected to a fixed force value during the welding process without considering the variations in the force conditions during the welding process.…”

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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A feedforward deflection compensation scheme coupled with an offline path planning for robotic friction stir welding

Cited by 12 publications

References 18 publications

Mathematical Simulating of the Process of Friction Stir Welding for the Manufacture of Tank Bottoms in Aerospace Construction

Mathematical Simulating of the Process of Friction Stir Welding for the Manufacture of Tank Bottoms in Aerospace Construction

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

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