Skip to main content
SpringerLink
Log in
Book cover

Power Electronics and Renewable Energy Systems pp 433–441Cite as

Performance Evaluation of Differential Evolution and Particle Swarm Optimization Algorithms for Optimizing Power Loss in a Worm Gear Mechanism

  • Conference paper
  • First Online:

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 326))

Abstract

Optimal design of machine elements plays a vital role in reducing the cost of manufacturing the machine elements. Design optimization is an important task to achieve the above goal. Many optimization algorithms have been proposed and used in the past for design optimization and they are used to find the optimal set of design variables possibly subjected to a set of constraints. Still, there is a scope for efficient algorithms for the design optimization of machine elements. In this study, the design optimization of a worm gear mechanism is presented by using two non-conventional optimization algorithms namely Differential Evolution and Particle Swarm Optimization algorithms for minimizing the power-loss. The results obtained by using Differential Evolution and Particle Swarm Optimization algorithms are compared with that of genetic algorithm and analytical method. The results showed that both the algorithms are efficient in finding the optimal design values.

This is a preview of subscription content, log in via an institution.

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   259.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   329.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD   329.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

References

  1. Storn R, Price K (1997) Differential evolution—a simple and efficient heuristic for global optimization over continuous spaces. J Global Optim 11:341–359

    Article  MATH  MathSciNet  Google Scholar 

  2. Kennedy V, Eberhart R (1995) Particle swarm optimization. In: Proceedings of the IEEE international conference on neural networks, pp 1942–1948

    Google Scholar 

  3. Deb K (1996) Optimization for engineering design: algorithms and examples. Prentice Hall, Englewood Cliffs

    Google Scholar 

  4. Bhandari VB (2010) Design of machine elements, McGraw Hill Education (India) Pvt Ltd

    Google Scholar 

  5. Gologlu C, Zeyveli M (2009) A genetic approach to automate preliminary design of gear drives. Comput Indus Eng 57:1043–1051

    Article  Google Scholar 

  6. Caballero S, Colomerand V, Romero R (2008) Cylindrical parallel gear trains design by means of genetic optimization. In: Selected proceedings from the 12th international congress on project engineering, pp 150–160

    Google Scholar 

  7. Chong TH, Lee JS (2000) A design method of gear trains using a genetic algorithm. Int J Korean Soc Precis Eng 1(1):62–70

    Google Scholar 

  8. Mendi F, Baskal T (2010) Optimization of module, shaft diameter and rolling bearing for spur gear through genetic algorithm. Expert Syst Appl 37:8058–8064

    Article  Google Scholar 

  9. Savsani V, Rao RV, Vakharia DP (2010) Optimal weight design of a gear train using particle swarm optimization and simulated annealing algorithms. Mech Mach Theory 45:531–541

    Article  MATH  Google Scholar 

  10. Akay B, Karaboga D (2012) Artificial bee colony algorithm for large-scale problems and engineering design optimization. J Intell Manuf 23:1001–1014

    Article  Google Scholar 

  11. Padmanabhan S, Chandrasekaran M, Srinivasa Raman V (2013) Worm gear drive optimization using modified artificial immune algorithm. J Curr Eng Res 3(1):48–51

    Google Scholar 

  12. Mogal YK, Wakchaure VD (2013) A multi-objective optimization approach for design of worm and worm wheel based on genetic algorithm. Bonfring Int J Man Mach Interface 3(1):8–12

    Article  Google Scholar 

  13. Su D, Peng W (2008) Optimum design of worm gears with multiple computer aided techniques. ICCES 6(4):221–227

    Google Scholar 

  14. Sabarinath P, Thansekhar MR, Saravanan R (2013) Performance evaluation of particle swarm optimization algorithm for optimal design of belt pulley system. Lecture notes in computer science, vol 8297, pp 601–616

    Google Scholar 

  15. Yaman M, Saruhan H, Mendi F (2006) Power loss optimization of a worm gear mechanism by using genetic algorithm. In: 11th international FIGES user conference for computer aided engineering and system modeling, Bolu, Turkey, 13–15 September, pp 1–7, ISBN 975-98408-2-0

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. K.L.N. College of Engineering, Pottapalayam, 630611, India

    P. Sabarinath & M. R. Thansekhar

  2. Sri Krishna College of Technology, Coimbatore, 641042, India

    R. Saravanan

Authors
  1. P. Sabarinath
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. M. R. Thansekhar
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. R. Saravanan
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to P. Sabarinath .

Editor information

Editors and Affiliations

  1. Electrical & Electronics, Rajalakshmi Engineering College, Chennai, Tamil Nadu, India

    C. Kamalakannan

  2. Electrical & Electronics Engineering, Noorul Islam College of Engineering, Kumaracoil, Tamil Nadu, India

    L. Padma Suresh

  3. Department of Electrical and Electronics Engineering, SRM University SRM Engineering College, Chennai, Tamil Nadu, India

    Subhransu Sekhar Dash

  4. Department of Electrical Engineering, Indian Institute of Technology, New Delhi, India

    Bijaya Ketan Panigrahi

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Springer India

About this paper

Cite this paper

Sabarinath, P., Thansekhar, M.R., Saravanan, R. (2015). Performance Evaluation of Differential Evolution and Particle Swarm Optimization Algorithms for Optimizing Power Loss in a Worm Gear Mechanism. In: Kamalakannan, C., Suresh, L., Dash, S., Panigrahi, B. (eds) Power Electronics and Renewable Energy Systems. Lecture Notes in Electrical Engineering, vol 326. Springer, New Delhi. https://doi.org/10.1007/978-81-322-2119-7_44

Download citation

  • DOI: https://doi.org/10.1007/978-81-322-2119-7_44

  • Published:

  • Publisher Name: Springer, New Delhi

  • Print ISBN: 978-81-322-2118-0

  • Online ISBN: 978-81-322-2119-7

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation