Corner-milling process parameter optimization regarding H62 brass using Kriging model and improved particle swarm optimization algorithm

2020 ◽  
Vol 42 (4) ◽  
Author(s):  
Junyu Meng ◽  
Yuan Wang ◽  
Qianfeng Liao ◽  
Yang Yang
Keyword(s):  
Particle Swarm Optimization ◽  
Parameter Optimization ◽  
Optimization Algorithm ◽  
Particle Swarm Optimization Algorithm ◽  
Kriging Model ◽  
Milling Process ◽  
Process Parameter ◽  
Swarm Optimization ◽  
Process Parameter Optimization ◽  
Improved Particle Swarm Optimization

scholarly journals Structure optimization design of a thin-film diffraction imaging system based on the Kriging model and the improved particle swarm optimization algorithm

2021 ◽  
Vol 12 (2) ◽  
pp. 875-889
Author(s):  
Yitian Wang ◽  
Liu Zhang ◽  
Huanyu Zhao ◽  
Fan Zhang
Keyword(s):  
Thin Film ◽  
Particle Swarm Optimization ◽  
Optimization Algorithm ◽  
Particle Swarm Optimization Algorithm ◽  
Imaging System ◽  
Kriging Model ◽  
Swarm Optimization ◽  
Improved Particle Swarm Optimization ◽  
Attitude Stability ◽  
Diffraction Imaging

Abstract. A thin-film diffraction imaging system is a type of space telescope imaging system with high resolution and loose surface tolerance often used in various fields, such as ground observation and military reconnaissance. However, because this system is a large and flexible multi-body structure, it can produce flexural vibration easily during the orbit operation, which has a serious effect on the attitude stability of the system and results in low pointing accuracy. Therefore, this study proposes an optimization method based on the Kriging model and the improved particle swarm optimization algorithm to improve the stability and optimize the structure of the entire system. Results showed the area–mass ratio of the thin-film diffraction imaging system decreased by 9.874 %, the first-order natural frequency increased by 23.789 %, and the attitude stability of the thin-film diffraction imaging system improved.

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