Design Optimisation Of Spur Gear Using Genetic Algorithm

Abstract

Gears are one of the most commonly used power transmission mechanisms in most types of machinery and. 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. In this study, a spur gear pair was modelled and was subjected to static structural analyses for varying gear material. Stress analyses and deformation analyses were performed for each material and the optimum design for reduced weight structural stability was chosen. The design was then subjected to optimisation by Genetic Algorithm. 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 centre 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 three type of materials, which are alloy steel, cast iron, and epoxy glass composites.