Abstract
The aim of this work is to present the great performance of the numerical algorithm of Particle Swarm Optimization applied to find the best teeth modifications for multimesh helical gears, which are crucial for the static transmission error (STE). Indeed, STE fluctuation is the main source of vibrations and noise radiated by the geared transmission system. The microgeometrical parameters studied for each toothed wheel are the crowning, tip reliefs and start diameters for these reliefs. Minimization of added up STE amplitudes on the idler gear of a three‐gear cascade is then performed using the Particle Swarm Optimization. Finally, robustness of the solutions towards manufacturing errors and applied torque is analyzed by the Particle Swarm algorithm to access to the deterioration capacity of the tested solution.
Highlights
The static transmission error (STE) under load [1] is defined as the difference between the actual position of the driven gear and its theoretical position for a very slow rotation velocity and for a given applied torque
Under load at very low speed, these situations result from tooth deflections, tooth surface modifications, and manufacturing errors
To reduce the radiated noise, the peak-to-peak amplitude of the STE fluctuation needs to be minimized by the mean of tooth modifications
Summary
The STE under load [1] is defined as the difference between the actual position of the driven gear and its theoretical position for a very slow rotation velocity and for a given applied torque. Its characteristics depend on the instantaneous situations of the meshing tooth pairs. Under load at very low speed (static transmission error), these situations result from tooth deflections, tooth surface modifications, and manufacturing errors. STE generates dynamic mesh force transmitted to shafts, bearings, and to the crankcase. The vibratory state of the crankcase is the main source of the radiated noise [2]. To reduce the radiated noise, the peak-to-peak amplitude of the STE fluctuation needs to be minimized by the mean of tooth modifications. It consists in micro-geometrical modifications listed below and displayed on Figure 1:
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