Multi-Objective Optimization of two-Stagehelical Geartrain

Abstract

Engineering design is an iterative process that requires to be followed with all designfeasible solutions in order to arrive at desire objective. Proper design of gear train has a significant place in power transmission applications. Thus, an attempt to automate preliminary design of gear train has been accomplished in the paper. In this paper, volume and load carrying capacity are optimized. Two different methodologies (i) Genetic algorithm (GA), (ii) Fminsearch Solver optimization techniqueare used to solve the problem. In the first two methods, volume is minimized at first stage and then the Maximization load carrying capacities of both shafts are calculated in second stage. In this study, the Genetic algorithm is introduced for the optimization purpose of gear trains to solve such problems and this system is applied for the geometrical volume (size) minimization problem of the two-stage gear train and the gear train to show that genetic algorithm is better than the conventional algorithms for solving the problems. Genetic algorithm is used for optimization by using a Matlab programs are used to solve the problem. For the optimization purpose, face width, module, and number of teeth are taken as design variables. Constraints are imposed on bending strength, fatigue strength, surface strength and interference. This result is validated with the experimental data results published in the literature and standard parameters of gear train.