RESEARCH ARTICLE

Multi-objective genetic algorithms based structural optimization and experimental investigation of the planet carrier in wind turbine gearbox

  • Pengxing YI ,
  • Lijian DONG ,
  • Tielin SHI
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  • School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China

Received date: 12 Sep 2014

Accepted date: 25 Oct 2014

Published date: 19 Dec 2014

Copyright

2014 Higher Education Press and Springer-Verlag Berlin Heidelberg

Abstract

To improve the dynamic performance and reduce the weight of the planet carrier in wind turbine gearbox, a multi-objective optimization method, which is driven by the maximum deformation, the maximum stress and the minimum mass of the studied part, is proposed by combining the response surface method and genetic algorithms in this paper. Firstly, the design points’ distribution for the design variables of the planet carrier is established with the central composite design (CCD) method. Then, based on the computing results of finite element analysis (FEA), the response surface analysis is conducted to find out the proper sets of design variable values. And a multi-objective genetic algorithm (MOGA) is applied to determine the direction of optimization. As well, this method is applied to design and optimize the planet carrier in a 1.5 MW wind turbine gearbox, the results of which are validated by an experimental modal test. Compared with the original design, the mass and the stress of the optimized planet carrier are respectively reduced by 9.3% and 40%. Consequently, the cost of planet carrier is greatly reduced and its stability is also improved.

Cite this article

Pengxing YI , Lijian DONG , Tielin SHI . Multi-objective genetic algorithms based structural optimization and experimental investigation of the planet carrier in wind turbine gearbox[J]. Frontiers of Mechanical Engineering, 2014 , 9(4) : 354 -367 . DOI: 10.1007/s11465-014-0319-5

Acknowledgements

This study was supported by the National High Technology Research and Development Program of China, (No. 2013AA040206).
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