Application of Adaptive Mutation Particle Swarm Optimization Algorithm in Roller Optimization
DOI:
https://doi.org/10.54097/4c03f405Keywords:
Particle Swarm Optimization, Roller, Optimized Design, MatlabAbstract
To solve the problems of excessive volume and weight of the double roll granulator, a volume function model was established with the key parameters of the double roll structure, which is the main component of the granulation mechanism, as variables. Through the Matlab software platform, combined with five constraint conditions including tooth surface contact fatigue, gear root cutting restriction, tooth root bending fatigue, straw particle cross-sectional size and surface area, the adaptive mutation particle swarm algorithm is used for iterative constraint optimization design. Compared with the original double roll structure model, the optimized design achieves more compact volume parameters while satisfying the constraints, effectively reducing the problems of excessive volume and weight of the double roll granulator.
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[1] Wang Chun, Han Jiahao, Jiqing. Research on Optimization Design of Gear Transmission Based on Improved Particle Swarm Optimization Algorithm [J]. Mechanical and Electrical Engineering,2021,38(02):239-244.
[2] Ma Honggang, Liu Huan, Lei Wenjun, etc. Optimization design of helical gears based on dual population genetic particle swarm algorithm [J]. Internal Combustion Engine and Parts, 2021 (11): 22-24.
[3] Liu Longjie, Liu Xiangzhen. Reliability optimization design of gear transmission based on genetic algorithm [J]. Agricultural Equipment and Vehicle Engineering, 2021, 59 (06): 101-103+108.
[4] Rao R V ,Pawar R B . Optimal Weight Design of a Spur Gear Train Using Rao Algorithms[M]. 2020.
[5] Chen Bowen, Zou Hai. Summative Adaptive Mutation Particle Swarm Optimization Algorithm [J/OL]. Computer Engineering and Applications: 1-11 [2021-07-23].
[6] Mao Tianyu, Yu Yong, Liu Huaiju, etc. Dynamic reliability analysis of gear transmission system for flying cars [J]. Mechanical Transmission, 2021, 45 (06): 96-103+176.
[7] Huang Xiaoping, Zhao Linlin. Root cutting analysis of cylindrical helical arc gears [J]. Mechanical Transmission, 2019, 43 (06): 29-36+54.
[8] Xu Guosheng, Xu Zuyong, Zhou Junjie, etc. Research on Path Planning Algorithm for Inspection Robots Based on Genetic Algorithm [J]. Mechanical Design and Manufacturing Engineering, 2021, 50 (06): 93-98.
[9] Min Xu. Analysis of Double Roll Granulation and Extrusion Forming Process [D]. Anhui University of Engineering, 2023.
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