Practical Optimal Design on Two Stage Spur Gears Train Using Nature Inspired Algorithms
N. Godwin Raja Ebenezer1, S. Ramabalan2, S. Navaneethasanthakumar3
1N. Godwin Raja Ebenezer*, Professor, Department of Mechanical Engineering, Loyola – ICAM College of Engineering and Technology, Chennai, Tamil Nadu, India.
2S. Ramabalan, Professor, Department of Mechanical Engineering, EGS Pillay Engineering College, Nagapattinam, Tamil Nadu, India.
3S. Navaneethasanthakumar, Professor, Department of Mechanical Engineering, MLR Institute of Technology, Hyderabad, (Telengana), India.
Manuscript received on July 20, 2019. | Revised Manuscript received on August 10, 2019. | Manuscript published on August 30, 2019. | PP: 4073-4081 | Volume-8 Issue-6, August 2019. | Retrieval Number: F8638088619/2019©BEIESP | DOI: 10.35940/ijeat.F8638.088619
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The accurate design of spur gear drive has a tremendous impact on size, weight, transmission and machine performance. Also, the demand for lighter gears is high in power transmission systems, as they save material and energy. Hence this paper presents an enhanced method to solve a two stage spur gear optimization problem. It consists of a mathematical model with a nonlinear objective function and 11 constraints. A two stage spur gear is considered. To obtain minimum volume of spur gear drive is objective of the problem. The considered design variables are: Module, number of teeth, base width of the gears and, shaft diameter and power. Besides considering regular mechanical constraints based on American Gear Manufacturers Association (AGMA) requisites, six more additional critical constraints on contact ratio, load carrying capacity, power loss, root not cut, no involute interference and line of action are imposed on the drive. Nature inspired optimization algorithms, namely, Simulated Annealing (SA), Firefly (FA) and MATLAB solver fmincon are used to find solution in MATLAB environment. Simulation results are analyzed, compared with literature and validated.
Keywords: Gear optimization, Spur gear drive, AGMA, Nature inspired algorithms.