Design optimisation of bevel gear pair

In this paper, an attempt has been made to optimise bevel gear pair design using a non-linear programming optimising software LINGO and meta-heuristics such as real coded genetic algorithm, ant colony optimisation and particle swarm optimisation algorithms. A combined objective function which maximises the power, efficiency and minimises the overall weight, centre distance has been considered in this model. The efficiency of the proposed algorithms is validated through gear design problems and the comparative results are studied.

[1]  Meng-Sing Liou,et al.  Progress in design optimization using evolutionary algorithms for aerodynamic problems , 2010 .

[2]  Darle W. Dudley,et al.  Practical gear design , 1954 .

[3]  Heike Trautmann,et al.  Statistical Methods for Improving Multi-objective Evolutionary Optimisation , 2009 .

[4]  Joong-Ho Shin,et al.  Optimal rotor wear design in hypotrochoidal gear pump using genetic algorithm , 2011 .

[5]  M. Jaberipour,et al.  Two improved harmony search algorithms for solving engineering optimization problems , 2010 .

[6]  Singiresu S Rao,et al.  MULTISTAGE MULTIOBJECTIVE OPTIMIZATION OF GEARBOXES. , 1986 .

[7]  Jeng-Shyang Pan,et al.  A Particle Swarm Optimization with Feasibility-Based Rules for Mixed-Variable Optimization Problems , 2009, 2009 Ninth International Conference on Hybrid Intelligent Systems.

[8]  Ellips Masehian,et al.  Particle Swarm Optimization Methods, Taxonomy and Applications , 2009 .

[9]  M. Chandrasekaran,et al.  Solving job shop scheduling problems using artificial immune system , 2006 .

[10]  Mehmet Bozca,et al.  Empirical model based optimization of gearbox geometric design parameters to reduce rattle noise in an automotive transmission , 2010 .

[11]  Marco Dorigo,et al.  Ant system: optimization by a colony of cooperating agents , 1996, IEEE Trans. Syst. Man Cybern. Part B.

[12]  R. Rao,et al.  Optimal weight design of a gear train using particle swarm optimization and simulated annealing algorithms , 2010 .

[13]  M. Sachithanandam,et al.  Genetic Algorithm (GA) for Multivariable Surface Grinding Process Optimisation Using a Multi-objective Function Model , 2001 .

[14]  Jean-Luc Marcelin,et al.  Integrated Optimization of Mechanisms with Genetic Algorithms , 2010 .

[15]  Zhong Wan,et al.  Global optimization design method for maximizing the capacity of V-belt drive , 2011 .

[16]  Alice M. Agogino,et al.  Theory of design: An optimization perspective , 1990 .

[17]  R. Saravanan,et al.  Optimization of Machining Parameters for Milling Operations Using Non-conventional Methods , 2005 .

[18]  Shu-Kai S. Fan,et al.  A parallel particle swarm optimization algorithm for multi-objective optimization problems , 2009 .

[19]  C. Innocenti A Framework for Efficiency Evaluation of Multi-Degree-of-Freedom Gear Trains , 1996 .

[20]  R. Saravanan,et al.  Machining Parameters Optimisation for Turning Cylindrical Stock into a Continuous Finished Profile Using Genetic Algorithm (GA) and Simulated Annealing (SA) , 2003 .

[21]  Daniel Schrage,et al.  A Systems Engineering Modeling and Simulation Approach for Rotorcraft Drive System Optimization , 2011 .