Affiliation:
1. K.L.N. College of Engineering
2. Sri Krishna College of Technology
Abstract
Mechanical design engineers design products by selecting the best possible materials and geometries that satisfies the specific operational requirements of the design. It involves lot of creativity and aesthetics to make better designs. A gear design makes the designer to compromise many design variables so as to arrive the best performance of a gear set. The best possible way for multi variable, Multiobjective gear design is to try design optimization. For many complex engineering optimization problems multi objective design optimization methods are used to simplify the design problem. In this paper, multiobjective design of helical gear pair transmission with objective functions namely volume of the small and large helical gear and opposite number of overlap ratio is taken into account. The design variables considered are normal module, helix angle, gear width coefficient and teeth number of small helical gear. A recent meta-heuristic algorithm namely parameter adaptive harmony search algorithm is applied to solve this problem using the weighted sum approach. It is evident from the results that the proposed approach is performing better than other algorithms.
Publisher
Trans Tech Publications, Ltd.
Reference11 articles.
1. S. Padmanabhan, Dr.M. Chandrasekaran, Dr. P. Asokan, Dr. V. Srinivasa Raman, A Performance Study of Real Coded Genetic Algorithm on Gear Design Optimization, Advanced Materials Research, Vols. 622-623, pp.64-68 (2013).
2. Tribhuwan Singh, Mohd. Parvez, Comparative Study Stress Analysis of Helical Gear using AGMA Standards and FEM, International Journal of Engineering Sciences & Research Technology, ISSN: 2277-9655 (2013).
3. B. Venkatesh, V. Kamala, A.M. K Prasad, Design, Modeling and Manufacturing of Helical gear, International Journal of Applied Engineering Research, ISSN 09764259, vol 1, N0. 1 (2010).
4. Sabarinath P, Thansekhar MR, Saravanan R, Performance evaluation of particle swarm optimization algorithm for optimal design of belt pulley system, Lecture notes in computer science, vol 8297, p.601–616 (2013).
5. Sabarinath P, Thansekhar MR, Saravanan R, Performance Evaluation of Differential Evolution and Particle Swarm Optimization Algorithms for Optimizing Power Loss in a Worm a gear Mechanism, Lecture Notes in Electrical Engineering, vol. 326, p.433 – 441 (2014).
Cited by
6 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献