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유전 알고리즘을 이용한 풍력발전기용 피치감속기의 최적 설계

Optimum Design of Pitch Reducer for Wind Turbine Using Genetic Algorithm

  • 김정길 (한국기계연구원 시스템신뢰성연구실) ;
  • 박영준 (한국기계연구원 시스템신뢰성연구실) ;
  • 이근호 (한국기계연구원 시스템신뢰성연구실) ;
  • 남용윤 (한국기계연구원 시스템신뢰성연구실) ;
  • 양우열 (효성 기어솔루션기술개발팀)
  • Kim, Jeong Gil (Dept. of System Reliability, Korea Institute of Machinery and Materials) ;
  • Park, Young Jun (Dept. of System Reliability, Korea Institute of Machinery and Materials) ;
  • Lee, Geun Ho (Dept. of System Reliability, Korea Institute of Machinery and Materials) ;
  • Nam, Yong Yun (Dept. of System Reliability, Korea Institute of Machinery and Materials) ;
  • Yang, Woo Yeoul (Gear Solution Technology Development Team, Hyosung)
  • 투고 : 2013.10.24
  • 심사 : 2013.12.10
  • 발행 : 2014.02.01

초록

유성기어의 설계는 모듈 등의 이산변수, 잇수 등의 정수 변수, 치폭, 종횡비 등의 연속 변수가 혼재된 복잡한 문제로 이를 해결하기 위해서는 최적 설계 기법이 적용되어야 한다. 본 연구에서는 유전 알고리즘(Genetic algorithm)을 이용한 최적 설계를 유성기어 설계에 적용하였다. 유성기어 설계시 기본이 되는 기어 잇수, 모듈, 압력각, 치폭 등과 같은 매크로 지오메트리(Macro-geometry)를 이용하여 이뿌리/치면 강도에 대한 강도 평가를 수행하였으며, 상용 프로그램과의 비교를 통해 검증하였다. 유전 알고리즘을 이용하여 기어의 체적을 최소화하기 위한 최적 설계를 수행하였으며, 이를 통하여 설계자는 초기 설계시 시행착오를 줄여 설계 시간을 단축시킬 수 있었다.

Planetary gear design is complex because it involves a combination of discrete variables such as module, integer variables such as the number of teeth, and continuous variables such as face width and aspect ratio. Thus, an optimum design technique is needed. In this study, we applied a genetic algorithm to the design optimization of a planetary gear. In this algorithm, tooth root strength and surface durability are assessed with fundamental variables such as the number of teeth, module, pressure angle, and face width. With the help of this technique, gear designers could reduce trial and error in the initial design stages, thus cutting the time required for planetary gear design.

키워드

참고문헌

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피인용 문헌

  1. A study on the design of cycloidal pitch reducer for the 2MW-class wind turbine vol.39, pp.9, 2015, https://doi.org/10.5916/jkosme.2015.39.9.895
  2. A Review of Recent Advances in Design Optimization of Gearbox vol.19, pp.11, 2018, https://doi.org/10.1007/s12541-018-0203-z