Optimum profile modifications of spur gears by means of genetic algorithms

Abstract An original application of Genetic Algorithms (GAs) is developed in order to optimize spur gear pairs toward vibration and noise reduction. The approach takes into account the most important parameters of micro-geometric modifications, namely tip and root relief, therefore the parameter space is eight dimensional. The objective function of the GA depends on the static transmission error (STE) that is related to teeth flexibility. STE is estimated by means of a nonlinear finite element approach: either the amplitude of the STE fluctuation or its harmonic content are considered as objective functions. The effectiveness of the approach is checked on an actual test case: GAs are able to find the optimum after a reasonable number of steps; such optimum is obtained on static basis and gives a strong vibration reduction. The reliability test proves that GAs lead to robust optima.