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Optimization Design of the Geared Rotor System With Critical Speed Constraints Using the Enhanced Genetic Algorithm

[+] Author Affiliations
T. N. Shiau, C. H. Kang, D. S. Liu, E. K. Lee

National Chung Cheng University, Chia Yi, Taiwan

W. C. Hsu

WuFeng Institute of Technology, Chia Yi, Taiwan

Paper No. GT2008-50754, pp. 1131-1136; 6 pages
doi:10.1115/GT2008-50754
From:
  • ASME Turbo Expo 2008: Power for Land, Sea, and Air
  • Volume 5: Structures and Dynamics, Parts A and B
  • Berlin, Germany, June 9–13, 2008
  • Conference Sponsors: International Gas Turbine Institute
  • ISBN: 978-0-7918-4315-4 | eISBN: 0-7918-3824-2
  • Copyright © 2008 by ASME

abstract

This paper presents an efficient enhanced genetic algorithm to minimize the shaft weight, the unbalance response and the response due to the transmission error simultaneously. The minimization plays an important role in designing the geared rotor system under critical speed constraints. In the process of optimization, the design variables consist of shaft inner radii, bearing stiffness and the gear mesh stiffness. The enhanced genetic algorithm of optimization comprises the Hybrid Genetic Algorithm (HGA) and the Interval Genetic Algorithm (IGA). The HGA deals with this optimal design problem and the IGA accomplishes the interval optimization design. The results show that the presented enhanced genetic algorithm can not only effectively reduce the shaft weight and the transmission error response, but also precisely determine the interval ranges of design variables with feasible corresponding objective error.

Copyright © 2008 by ASME

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