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Optimization of Square-shaped Bolted Joints Based on Improved Particle Swarm Optimization Algorithm
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Faculty of Materials and Manufacturing, Beijing University of Technology, China
Beijing Institute of Aerospace Control Devices, China
XCMG Construction Machinery, China
Submission date: 2023-03-21
Final revision date: 2023-04-14
Acceptance date: 2023-06-18
Online publication date: 2023-07-05
Publication date: 2023-07-05
Corresponding author
Yongsheng Zhao   

Faculty of Materials and Manufacturing, Beijing University of Technology, Beijing, China
Eksploatacja i Niezawodność – Maintenance and Reliability 2023;25(3):168487
  • Establish the dynamics model of square bolt connection based on fractal theory.
  • An improved particle swarm optimization algorithm considering the influence of time-varying weight and contraction factor is proposed.
  • Compared with the traditional algorithm, the improved optimization algorithm shows better operational performance.
  • Meanwhile, the global stiffness optimization of the square bolt connection is realized
The bolted joint is widely used in heavy-duty CNC machine tools, which has huge influence on working precision and overall stiffness of CNC machine. The process parameters of group bolt assembly directly affect the stiffness of the connected parts. The dynamic model of bolted joints is established based on the fractal theory, and the overall stiffness of joint surface is calculated. In order to improve the total stiffness of bolted assembly, an improved particle swarm optimization algorithm with combination of time-varying weights and contraction factor is proposed. The input parameters are preloading of bolts, fractal dimension, roughness, and object thickness. The main goal is to maximize the global rigidity. The optimization results show that improved algorithm has better convergence, faster calculation speed, preferable results, and higher optimization performance than standard particle swarm optimization algorithm. Moreover, the global rigidity optimization is achieved.
The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the National Natural Science Foundation of China (No.52075012) and the Open Fund of Aerospace Servo Drive and Transmission Technology Laboratory (LASAT-20210103).
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