Title : ( Optimum design of straight bevel gears pair using evolutionary algorithms )
Authors: A. Zolfaghari , Masoud Goharimanesh , Ali Akbar Akbari ,Abstract
Straight bevel gear is a type of gear which is widely used in mechanical systems to transmit power between perpendicular rotating axes. Designing straight bevel gears with the least possible volume is of great importance in industry since it results in a decrease in energy consumption and the material requirement in manufacturing. In this paper, employing two powerful optimization algorithms, simulated annealing algorithm (SA) and genetic algorithm (GA), techniques for advanced optimization, coupled with American Gear Manufacturers Association (AGMA) instructions the volume of straight bevel gears pair is minimized and the corresponding design variables are obtained. These variables include majors, including teeth number, module and face width. Using a traditional technique, recommended values of the design variables by AGMA, a design example was performed and the values were obtained. Then, the suggested techniques were utilized to get the values. The comparison between the results of all techniques shows that proposed optimization algorithms are considerably capable of minimizing the volume. It indicates that improvement in the attained volume varies between 1.56 and 17.40% for SA and 9.28 and 23.15% for GA.
Keywords
, Straight bevel gear, Optimum design, Simulated annealing algorithm, Genetic algorithm, AGMA@article{paperid:1063003,
author = {A. Zolfaghari and Goharimanesh, Masoud and Akbari, Ali Akbar},
title = {Optimum design of straight bevel gears pair using evolutionary algorithms},
journal = {Journal of the Brazilian Society of Mechanical Sciences and Engineering},
year = {2017},
volume = {39},
number = {6},
month = {June},
issn = {1678-5878},
pages = {2121--2129},
numpages = {8},
keywords = {Straight bevel gear; Optimum design; Simulated annealing algorithm; Genetic algorithm; AGMA},
}
%0 Journal Article
%T Optimum design of straight bevel gears pair using evolutionary algorithms
%A A. Zolfaghari
%A Goharimanesh, Masoud
%A Akbari, Ali Akbar
%J Journal of the Brazilian Society of Mechanical Sciences and Engineering
%@ 1678-5878
%D 2017