Optimization of Square-shaped Bolted Joints Based on Improved Particle Swarm Optimization Algorithm

• Autorzy: Chen Kui , Yang Cheng , Zhao Yongsheng , Niu Peng , Niu NaNa , Wu Hongchao

Identyfikatory

DOI

10.17531/ein/168487

• Języki publikacji: EN

Abstrakty

EN

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.

Słowa kluczowe

EN

particle swarm optimization algorithm; bolt connection; bolted joint; fractal theory

• Wydawca: Polskie Naukowo-Techniczne Towarzystwo Eksploatacyjne
• Czasopismo: Eksploatacja i Niezawodność
• Rocznik: 2023
• Tom: Vol. 25, no. 3
• Strony: art. no. 168487
• Opis fizyczny: Bibliogr. 28 poz., rys., tab., wykr.

Twórcy

autor

Chen Kui

• Faculty of Materials and Manufacturing, Beijing University of Technology, China

autor

Yang Cheng

• Beijing Institute of Aerospace Control Devices, China

autor

Zhao Yongsheng

• Faculty of Materials and Manufacturing, Beijing University of Technology, China

autor

Niu Peng

• Faculty of Materials and Manufacturing, Beijing University of Technology, China

autor

Niu NaNa

• Faculty of Materials and Manufacturing, Beijing University of Technology, China

autor

Wu Hongchao

• XCMG Construction Machinery, China

Bibliografia

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Uwagi

Opracowanie rekordu ze środków MNiSW, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2024).