Open AccessOptimization of helicopter blade section based on multi-objective optimization algorithm
Author(s) -
Shuai Wang,
Guohua Wang
Publication year - 2019
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1419/1/012036
Subject(s) - sorting , blade (archaeology) , section (typography) , genetic algorithm , stiffness , convergence (economics) , algorithm , multi objective optimization , computer science , structural engineering , mathematical optimization , mathematics , engineering , operating system , economics , economic growth
This paper aims to find a better performance multi-objective optimization algorithm to optimize the helicopter blade section structure, so that the optimized blade section characteristics are better. Optimization objectives include the section quality linear density of the blade and the section stiffness characteristics of the blade. In this paper, three multi-objective optimization algorithms including non-dominated sorting genetic algorithm II (NSGA-II), non-dominated sorting genetic algorithm III (NSGA-III) and multi-objective evolutionary algorithm based on decomposition (MOEA/D) algorithm are used to optimize the blade section. The performance evaluation results of the three algorithms are evaluated by inverted generation distance(IGD). The calculation results show that the MOEA/D algorithm has better convergence, uniformity and extensiveness, and the comprehensive performance is better than other algorithms in high-dimensional multi-objective optimization. After optimization by the algorithm, the quality linear density of the section is reduced by 1.8%, the torsional stiffness of section is increased by 2.1%., the shimming stiffness of section is decreased by 1.9%, the waving stiffness of section is decreased by 1.7%, and the tensile stiffness is increased by 0.9 %.