Volume optimization of gear trains with spur gears using genetic algorithm

Abstract

Abstract. Gear train volume optimization presents a complex problem tied to practical application in gear train manufacturing. This paper is oriented on the analysis of the problem of gear train volume minimization from a shaft axes positioning aspect. An original mathematical model has been developed where the objective function gives a minimum volume with changed shaft (spur gear) axes positions, while at the same time complying with all physical constraints. An original optimization software has also been developed using RCGA (Real Coded Genetic Algorithm) optimization methods. The general mathematical model was applied to three real conceptions of gear train as well as a comparative analysis of initial and optimal values. The results show a decrease of volume being directly linked to a decrease of not only space but material used to make the housing, costs, documentation formulation rate, etc.

Solving a Multi-Objective Optimization Problem of a Two-Stage Helical Gearbox with Second-Stage Double Gear Sets Using the MAIRCA Method

“…Research on helical gearbox optimization has been fairly extensive up to this point on both single-objective and multi-objective optimization problems. The single-objective optimization problems have been conducted with different objectives, including increasing gearbox efficiency [2,3], reducing radiated noise [4][5][6], gear box length [7][8][9][10], gearbox height [11], gearbox volume [8][9][10][11][12], gear mass [11,13,14], gearbox cross-section area [15][16][17][18],…”

“…2024, 14, 5274 2 of 18 and gearbox cost [19][20][21]. The research was conducted for two-stage [2,3,[7][8][9][10], threestage [14,18,22], and four-stage gearboxes [9,21]. Solving the MOOP for the helical gearbox, in particular, is highly studied as, in practice, a gearbox can only be satisfied by a large number of objective functions.…”

Development of a Statistical Reliability-Based Model for the Estimation and Optimization of a Spur Gear System

“…Barbieri et al (2008) applied two optimization strategiesthe static finite element calculations and the numerical ODE integration methodto model the spur gear noise reduction, where the STE and dynamic transmission error are optimized via genetic algorithms. Marjanović et al (2017) applied a real-coded genetic algorithm method to study and optimize the gear train volume of a gear system. The objective function is used to minimize the volume with changes in the position of the shaft axes, at the same time comply with all physical constraints.…”