Volume 32 Issue 6
Jun.  2017
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Vibration reduction optimization of gear modification based on Kriging model and genetic algorithm[J]. Journal of Aerospace Power, 2017, 32(6): 1412-1418. doi: 10.13224/j.cnki.jasp.2017.06.018
Citation: Vibration reduction optimization of gear modification based on Kriging model and genetic algorithm[J]. Journal of Aerospace Power, 2017, 32(6): 1412-1418. doi: 10.13224/j.cnki.jasp.2017.06.018

Vibration reduction optimization of gear modification based on Kriging model and genetic algorithm

doi: 10.13224/j.cnki.jasp.2017.06.018
  • Received Date: 2016-09-20
  • Publish Date: 2017-06-28
  • To solves the problems of large computation, low precision and complicated operation during optimization of gear modification, an algorithm for optimization of gear modification was proposed based on Kriging model and genetic algorithm. Taking spur gear drive as the research object, optimization of gear modification was carried out. Firstly, in order to solve the problems of multiple responses and implicit function during optimization of gear modification, Kriging model was established by using Latin sampling method. Compared with the gear engaged stiffness of Kriging prediction and finite element, it was shown that the maximum errors of predicted stiffness parameters were 7.79×10-5, 1.20×10-3 and 1.30×10-4 respectively, therefore, the precision of Kriging multiple prediction was validated. Secondly, Kriging prediction was applied to dynamical differential equation of spur gear, and then fluctuation of dynamic transmission error was regarded as the goal of genetic algorithm optimization, so optimal parameters of gear modification was obtained. Example showed that the proposed method was better than ISO(International Standardization Organization) modification and no modification, therefore, the efficiency and correctness of the gear modification by using genetic algorithm and Kriging model was validated. Compared with gear modification by using finite element directly, the cost time of the proposed method changed from 26.91d to 2.24h, so the computational efficiency of the proposed method was verified.

     

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