Issue |
MATEC Web Conf.
Volume 317, 2020
7th International BAPT Conference “Power Transmissions 2020”
|
|
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Article Number | 01004 | |
Number of page(s) | 8 | |
Section | Design, Analysis, Simulation and Optimization | |
DOI | https://doi.org/10.1051/matecconf/202031701004 | |
Published online | 03 August 2020 |
Solving the problem of optimal design for a two-stage reducer by using a modified evolutionary algorithm
National Technical University “Kharkiv Polytechnic Institute”, Department of Theory and Computer-Aided Design of Mechanisms and Machines, 61002 Kharkiv, Ukraine
* Corresponding author: ustin1964@gmail.com
The work is devoted to solving the problem of selecting optimal geometric parameters of gears of a two-stage cylindrical reducer using a modified evolutionary algorithm (EA).
The statement of the problem is considered, design parameters, objective functions, limitations on design parameters are determined. This allowed us to propose a modification of EA. To generate the initial test points, it was proposed to use the LP-τ sequence, this allowed us to reduce the initial population of test points and bring EA closer to a truly “random” process.
The scheme of the proposed algorithm is considered, which gives an idea of the sequence of operations that are carried out with populations of test points at each stage of the evolutionary process.
The solution of the specific problem of selecting optimal parameters for a serial reducer is given. The input data, numerical and functional limitations are determined, the objective functions are formed. The results of the solution are shown in several presentation formats: tabular and graphical, which allows to qualitatively interpret and analyze the results.
Conclusions are made about testing the proposed algorithm for solving a specific problem of optimal design. Further ways of improving this methodology are proposed.
© The Authors, published by EDP Sciences, 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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