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The multi-objective optimization design for the magnetic adsorption unit of wall-climbing robot

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Abstract

The motion stability and mass of the magnetic crawler wall-climbing robot usually affects the working performance of robot. In this study, the structure of the magnetic adsorption unit (MAU) is optimized based on the virtual prototyping technology to improve the working performance of robot. Firstly, the dynamic simulation model of the robot considering magnetic variation is established, and the model is verified by experiments. Based on the model, the objective function of the optimization model is established by DOE and surrogate model method. Then, through the force analysis of the robot, the minimum adsorption force required by each MAU is obtained, which is used as the constraint condition of the optimization model. Finally, the NSGA-II is used to solve the optimization model, and the results show that the vibration amplitude is reduced by 6.49 %, and the mass of the MAU is reduced by 9.66 %.

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Abbreviations

B :

The width of the MAU

L :

The length of the MAU

H :

The height of the MAU

ϕ :

The rotation angle between the MAU and the aluminum alloy rotating seat

Obj 1 (x) :

The objective function (vibration amplitude) of the optimization model

Obj 2 (x) :

The objective function (mass) of the optimization model

F i :

The magnetic adhesion force when the i-th MAU will to be attached to or separated from the wall

F 2 :

The function of the second MAU between the magnetic force and the time in multi-body dynamics simulation software

Y(x) :

The functional relationship between the amplitude and the optimization variables

F(x) :

The functional relationship between the magnetic force and the optimization variables

G(x) :

The functional relationship between the mass of the magnet and the optimization variables

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Acknowledgments

This work is supported by the Central Government Guided Local Science and Technology Development Fund (Basic Research Project) 206Z1804G and the Funds for Creative Research Groups of Hebei Province, No. E2020202142, (reliability of electrical equipment).

Author information

Authors and Affiliations

  1. State Key Laboratory of Reliability and Intelligence of Electrical Equipment, Hebei University of Technology, Tianjin City, 300401, China

    Zhihao Zhao, Yourui Tao & Jia Wang

  2. School of Mechanical Engineering, Hebei University of Technology, Tianjin City, 300401, China

    Zhihao Zhao, Yourui Tao & Jia Wang

  3. College of Mechanical and Vehicle Engineering, Hunan University, Chang-sha City, 410082, China

    Junyu Hu

Authors
  1. Zhihao Zhao
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  2. Yourui Tao
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  3. Jia Wang
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Corresponding author

Correspondence to Yourui Tao.

Additional information

Yourui Tao is a Professor within HeBei University of Technology, Tianjin, China. His research interests are in the area of reliability theory and methods, multidisciplinary optimization design and advanced composite materials.

Zhihao Zhao is a student currently pursuing the Master degree in HeBei University of Technology, Tianjin, China. His current research interests are in mechanical design and structural optimization design.

Wang Jia is an Assistant Professor within HeBei University of Technology, Tianjin, China. Her main research directions are degradation modeling and reliability assessment, industrial robot reliability and fault diagnosis.

Junyu Hu is a student currently pursuing the Ph.D. degree in Hunan University, Changsha City, China. His current research interests are in mechanical design and intelligent control of the magnetic crawler wall-climbing robot.

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Zhao, Z., Tao, Y., Wang, J. et al. The multi-objective optimization design for the magnetic adsorption unit of wall-climbing robot. J Mech Sci Technol 36, 305–316 (2022). https://doi.org/10.1007/s12206-021-1228-2

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  • DOI: https://doi.org/10.1007/s12206-021-1228-2

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