Optimization of Excitation Frequencies of a Gearbox Using Algorithms Inspired by Nature
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This work presents a methodology to enhance the preliminary design of a single-stage gearbox by diminishing the dynamic load between gears and bearings.
The gearbox dynamic load decreases by separating its excitation frequencies; the proposed methodology satisfies the design parameters like power, speed, and useful life and optimizes the distribution of the excitation frequencies using algorithms based on nature as particle swarm optimization, genetic algorithms and bat algorithm.
The algorithms maximize the separation between consecutive frequencies, even though the space of solutions has abrupt changes and discontinuities. The algorithm based on particle swarm optimization is the most stable and quick to converge.
As shown in this work, the dynamic load produced by the interaction between the gearbox components can be diminished from the design stage. The methodology based on nature algorithms improves the distribution of excitation frequencies, and therefore, decreases the possibility of a nonlinear synchronization, resonances and beating frequencies; thus prolongs the life of the transmission components.
KeywordsExcitation frequency Gearbox design Optimization
The authors thank CONACYT for supporting them.
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