Genetic Algorithm Approach for Spur Gears Design Optimization

Abstract

Gears are used in most types of machinery and vehicles for the power transmission system. The design of gears is highly complicated involving the satisfaction of many constraints such as strength, pitting resistance, bending stress, scoring wear, and interference in involute gears. In addition, using conventional or traditional optimization techniques to solve this problem could not give optimum results. A stochastic approach as a Genetic Algorithm (GA) is applied in this paper to find the optimal combination of design parameters for minimum weight of spur gears. The purpose of this study is minimizing the weight and the center distance of one pair of spur gears. This objective was accomplished by the means of the GA under some constraint such as bending strength, a contact stress and each dimension conditions of gears, which must be satisfied. The results are calculated by using Matlab tools of Genetic algorithm with four type of materials, which are standard steel, stainless steel, gray cast iron, and Alloy copper.