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The clamping position optimization and deformation analysis for an antenna thin wall parts assembly with ASA, MIGA and PSO algorithm

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Abstract

In order to reduce the deformation and assembly error in an antenna thin wall parts assembly process, the assembly location or clamping positions need to be optimized. In this paper, the effect of clamping positions and clamping force on the thin wall parts deformation is analyzed considering the gravity by finite element simulation under different clamping force. The clamping positions are optimized with the Adaptive Simulated Annealing (ASA), Multi-Island Genetic Algorithm (MIGA) and Particle Swarm Optimization (PSO) algorithm by Isight software to reduce the deformation. Comparing with MIGA and PSO method, the results show that the clamping position optimization based on ASA exhibits the better results and superior than the MIGA and PSO no matter whether it has the effect of gravity. Simultaneously, through establishing the contact force model and contact deformation model, the nonlinear relationship between contact force, contact deformation and contact area is qualitatively analyzed, and the node deformation is calculated by theoretical formula. Comparing with those results, it is shown that the theoretical value matches well with the simulation results. Finally, some clamping scheme principles are proposed so that it provides a basis for reducing the deformation and assembly error of thin wall parts in future.

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Authors and Affiliations

  1. School of Mechanical Engineering, Southeast University, Nanjing, 211189, China

    Ming-hui Pan, Wen-cheng Tang, Yan Xing & Jun Ni

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  1. Ming-hui Pan
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  2. Wen-cheng Tang
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  3. Yan Xing
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  4. Jun Ni
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Correspondence to Wen-cheng Tang.

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Pan, Mh., Tang, Wc., Xing, Y. et al. The clamping position optimization and deformation analysis for an antenna thin wall parts assembly with ASA, MIGA and PSO algorithm. Int. J. Precis. Eng. Manuf. 18, 345–357 (2017). https://doi.org/10.1007/s12541-017-0042-3

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  • DOI: https://doi.org/10.1007/s12541-017-0042-3

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