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Optimal Design of High-Voltage Disconnecting Switch Drive System Based on ADAMS and Particle Swarm Optimization Algorithm

Author

Listed:
  • Benxue Liu

    (School of mechanical and power engineering, Zhengzhou University, Zhengzhou 450001, China)

  • Peng Yuan

    (School of mechanical and power engineering, Zhengzhou University, Zhengzhou 450001, China)

  • Mengjian Wang

    (School of mechanical and power engineering, Zhengzhou University, Zhengzhou 450001, China)

  • Cheng Bi

    (School of mechanical and power engineering, Zhengzhou University, Zhengzhou 450001, China)

  • Chong Liu

    (School of mechanical and power engineering, Zhengzhou University, Zhengzhou 450001, China)

  • Xia Li

    (School of mechanical and power engineering, Zhengzhou University, Zhengzhou 450001, China)

Abstract

This paper focuses on the analysis of the stability of the GW17 high-voltage disconnecting switch drive system. Firstly, the optimization model of the disconnector is established, and the simulation analysis is carried out by ADAMS (Automatic Dynamic Analysis of Mechanical Systems) and the simulation results are verified by experiments. Afterwards, ADAMS optimization design and particle swarm optimization algorithm (PSO) are used to optimize the drive system of the disconnector, and the results are verified on the experimental platform. After optimization, the space rod is reduced by 15 mm, the minimum corner angle of the lower conductive rod is reduced by 71.0%, the minimum folding arm angle is reduced by 88.7% and the maximum force of the ball pair is reduced by 35.7%, which realizes the lightweight of the rod, reduces the wear of the ball pair, and improves the stability of the equipment operation.

Suggested Citation

  • Benxue Liu & Peng Yuan & Mengjian Wang & Cheng Bi & Chong Liu & Xia Li, 2021. "Optimal Design of High-Voltage Disconnecting Switch Drive System Based on ADAMS and Particle Swarm Optimization Algorithm," Mathematics, MDPI, vol. 9(9), pages 1-20, May.
    • Handle: RePEc:gam:jmathe:v:9:y:2021:i:9:p:1049-:d:549578
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    References listed on IDEAS

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    1. Wu, Zeping & Wang, Donghui & Okolo N, Patrick & Hu, Fan & Zhang, Weihua, 2016. "Global sensitivity analysis using a Gaussian Radial Basis Function metamodel," Reliability Engineering and System Safety, Elsevier, vol. 154(C), pages 171-179.
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