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Design Optimization of Two Stage Spur Gear Box with Critical Mechanical and Tribological Constraints by Nature Inspired Algorithms
An efficient spur gear box design should be reliable, versatile and satisfying strength requirements. In the presented article, a classy spur gear optimization problem for a two-step gear box taking into account such requirements is solved. The problem has a single nonlinear objective function, twenty one critical mechanical constraints including tribological aspects and eleven design variables. The central objective is to minimize volume of drive. Module, teeth number, base width, shaft diameter and power of the gearbox are chosen as design variables. The nature inspired algorithms, namely, Simulated Annealing (SA), Firefly Algorithm (FA) and Particle Swarm Optimization (PSO) are applied in MATLAB environment along with Fmincon. Simulation with and without tribological conditions are analysed and validated with literature. Results show that the volume reductions are higher in the case of SA, PSO, FA, and fmincon with decreasing orders of 17.90%, 17.84%, 16.17%, and 13.22% respectively without tribological constraints. These values are found to be higher than all the algorithms with tribological constraints.
Design Optimization of Two Stage Spur Gear Box with Critical Mechanical and Tribological Constraints by Nature Inspired Algorithms
An efficient spur gear box design should be reliable, versatile and satisfying strength requirements. In the presented article, a classy spur gear optimization problem for a two-step gear box taking into account such requirements is solved. The problem has a single nonlinear objective function, twenty one critical mechanical constraints including tribological aspects and eleven design variables. The central objective is to minimize volume of drive. Module, teeth number, base width, shaft diameter and power of the gearbox are chosen as design variables. The nature inspired algorithms, namely, Simulated Annealing (SA), Firefly Algorithm (FA) and Particle Swarm Optimization (PSO) are applied in MATLAB environment along with Fmincon. Simulation with and without tribological conditions are analysed and validated with literature. Results show that the volume reductions are higher in the case of SA, PSO, FA, and fmincon with decreasing orders of 17.90%, 17.84%, 16.17%, and 13.22% respectively without tribological constraints. These values are found to be higher than all the algorithms with tribological constraints.
Design Optimization of Two Stage Spur Gear Box with Critical Mechanical and Tribological Constraints by Nature Inspired Algorithms
J. Inst. Eng. India Ser. C
Ebenezer, N. Godwin Raja (Autor:in) / Ramabalan, S. (Autor:in) / Navaneethasanthakumar, S. (Autor:in)
01.02.2025
15 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
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