Parameter correlation analysis and minimum volume design of a helical gear implementing PSO algorithm
by Edmund Shingirayi Maputi; Rajesh Arora
International Journal of Forensic Software Engineering (IJFSE), Vol. 1, No. 2/3, 2020

Abstract: Gears are important mechanical elements in the assembly and functionality of a machine. The application of optimisation techniques in engineering design and gear technology has increased due to the accessibility and advancement in computational resources. Furthermore, current research trends reflect a keen interest in volume minimisation of gear systems. In this research work, a helical gear volume model is investigated. Particle swarm optimisation algorithm is applied and the results are compared and validated using an analytical method and geometric modelling software. Optimal design theory is discussed including the interrelation of concepts such as design, analysis and optimisation reflecting the need to analyse the influence of parameters on objectives. Experimental runs using genetic algorithm, firefly algorithm and teaching learning-based algorithm were also performed with statistical analysis. Parameter variation studies were also performed on each variable against the objective, minimum volume. The results of this research work, shows that module, pinion tooth number and face width are important parameters for the minimisation of gear weight with 38%, 32% and 12% contribution to variation, respectively.

Online publication date: Mon, 26-Oct-2020

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