Optimum design of straight bevel gears pair using evolutionary algorithms

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 materi...

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Bibliographic Details
Published inJournal of the Brazilian Society of Mechanical Sciences and Engineering Vol. 39; no. 6; pp. 2121 - 2129
Main Authors Zolfaghari, Abolfazl, Goharimanesh, Masoud, Akbari, Ali Akbar
Format Journal Article
LanguageEnglish
Published Berlin/Heidelberg Springer Berlin Heidelberg 01.06.2017
Springer Nature B.V
Subjects
Bevel gears
Computer simulation
Energy consumption
Engineering
Evolutionary algorithms
Gears
Genetic algorithms
Machine tools
Mechanical Engineering
Mechanical systems
Optimization
Simulated annealing
Technical Paper
Teeth
Simulated annealing algorithm
Optimum design
Straight bevel gear
AGMA
Genetic algorithm
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Summary: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.
ISSN:1678-5878
1806-3691
DOI:10.1007/s40430-017-0733-9