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Optimum Power Loss Analysis of Radial Magnetic Bearing using Multi-Objective Genetic Algorithm

by Santosh Shelke, R.V.Chalam
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 27 - Number 6
Year of Publication: 2011
Authors: Santosh Shelke, R.V.Chalam
10.5120/3305-4525

Santosh Shelke, R.V.Chalam . Optimum Power Loss Analysis of Radial Magnetic Bearing using Multi-Objective Genetic Algorithm. International Journal of Computer Applications. 27, 6 ( August 2011), 20-27. DOI=10.5120/3305-4525

@article{ 10.5120/3305-4525,
author = { Santosh Shelke, R.V.Chalam },
title = { Optimum Power Loss Analysis of Radial Magnetic Bearing using Multi-Objective Genetic Algorithm },
journal = { International Journal of Computer Applications },
issue_date = { August 2011 },
volume = { 27 },
number = { 6 },
month = { August },
year = { 2011 },
issn = { 0975-8887 },
pages = { 20-27 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume27/number6/3305-4525/ },
doi = { 10.5120/3305-4525 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:13:32.681264+05:30
%A Santosh Shelke
%A R.V.Chalam
%T Optimum Power Loss Analysis of Radial Magnetic Bearing using Multi-Objective Genetic Algorithm
%J International Journal of Computer Applications
%@ 0975-8887
%V 27
%N 6
%P 20-27
%D 2011
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In this paper, weight optimization of radial magnetic bearing (RMB) for varying poles has been carried out using multi-objective genetic algorithms (MOGAs). The total weight of RMB and copper loss has been selected as the minimization type objective function. The maximum space available, saturation flux density, the maximum current densities that can be supplied in the coil and the load to be lifted have been chosen as constraints. The coil space radius, pole tip radius, radial length of coil and number of poles has been proposed as design variables. Apart from the comparison of performance parameters in the form of figures and tables, designs are also compared through line diagrams. Post-processing has been done on the final optimized population by studying the variation of different parameters with respect to objective functions. A criterion for the choice of one of the best design based on the minimum weight of bearing showing optimum copper loss.

References
  1. Bakay L., and Dubois M., “Losses in an optimized 8-pole radial magnetic bearing for long term flywheel energy storage”, IEEE transaction on magnetic, Canada, 2007,3-5.
  2. Bakay L., Dubois M., and Ruel J, “Mass-Loss relationship optimized 8-pole AMB for long term flywheel energy storage”, IEEE AFRICON, Kenya, 2009,.2-3.
  3. V.D. Bloodgood, Jr., N.J. Groom, C.P. Britcher, “Further Development of an Optimal Design Approach Applied to Axial Magnetic Bearings”, NASA-2000-7ismb-vdb.
  4. H. Chang, S.C. Chung, “Integrated Design of Radial Active Magnetic Bearing Systems using Genetic Algorithms, Mechatronics”, vol. 12(1), 2002, 19-36.
  5. S. Ghanmi, M. Guedri, M.-L. Bouazizi, N. Bouhaddi, Use of Metamodels in the Multi-Objective Optimization of Mechanical Structures with Uncertainties, International Journal for Computational Methods in Engineering Science and Mechanics, vol. 8(5), 2007, 283-302.
  6. Jagu S.Rao, Rajiv Tivari, “Optimum design and analysis of thrust magnetic beating using genetic Algorithm”, International Journal for Computational Methods in Engineering Science and Mechanics, vol. 9, 2008, 223-245.
  7. C.A.C. Coello, “An Updated Survey of GA-Based Multiobjective Optimization Techniques,” ACM Computing Surveys, vol.32 (2), pp.109-143, 2000.
  8. K. Deb, A. Pratap, S. Agarwal, T. Meyarivan, “A Fast and Elitist Multiobjective Genetic Algorithm”, NSGA-II, IEEE Trans. Evol. Comput, vol. 6, 2002, 182-197.
  9. C.M. Fonseca, P.J. Fleming, “An Overview of Evolutionary Algorithms in Multi-objective Optimization, Evolutionary Computation”, Springer, vol. 3(1), 1995, 1-16.
  10. L.T. Bui, J. Branke, H.A. Abbas, “Multiobjective Optimization for Dynamic Environments,” IEEE Paper No. 0-7803-9363-5/05, 2005, 2349-2356.
  11. Y. GAO, L. Shi, P. Yao, “Study on Multi-Objective Genetic Algorithm”, Proc.3rd World Cong. On intelligent Control and Automation, 2000, 646-650.
  12. X. Hu, Z. Huang, Z. Wang, “Hybridization of the Multi-Objective Evolutionary Algorithms and the Gradient-based Algorithms”, IEEE Paper No.0-7803-7804-0 /03, 2003, 870-877.
  13. B.R.Rao, R.Tiwari, “Optimum design of rolling element bearing using genetic algorithm,” Mechanism and machine theory, 2007, 233-250.
  14. C.L. Malone, “Power to Weight Optimization for Magnetic Bearings,” Magnetic Bearings, Magnetic Drives and Dry Gas Seals Conference & Exhibition, Alexandria, Virginia, July, 1993.
  15. Ying Gao, Lei Shi, Pinging Yao, “Study on Multiobjective Genetic Algorithm,” IEEE transaction on Intelligent control and Automation, China, 2000, 646-650.
  16. R.T.marler, J.S.Arora, “Survey of multiobjective optimization methods for engineering,” Springer,Vol 26,2004,369-395.
  17. Tomoharu Nakashima, Hisao Ishibuchi, “Genetic algorithm based approaches for finding the minimum reference set for nearest neighbor classification,IEEE,1998,709-714.
  18. Deepti Chafekar, Liang shi, Jiang Xuan, “multiobjective genetic algorithm optimization using reduced models, IEEE transaction on system, Vol 35(2), 2005, 261-265.
  19. Santosh shelke, R.V.Chalam, “Optimum energy loss in electromagnetic bearing”, IEEE, vol.3, 2011,.374-378.
  20. E.H.Maslen, “Text book on Magnetic Bearings, University of Virginia, 36(4), 2000, 1009-1013.
  21. Santosh shelke, R.V.Chalam, “Optimum copper loss analysis of eight pole radial magnetic bearing: Multi objective genetic algorithm”, accepted for Springer, Proceeding of International conf. ccpe 2011.
Index Terms

Computer Science
Information Sciences

Keywords

Radial Magnetic Bearings Genetic Algorithms Optimum Design Multi-Objective Optimization

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