Volume 37 Issue 3
Mar.  2011
Turn off MathJax
Article Contents
Liu Hongmei, Lü Chen, Ouyang Pingchao, et al. Helicopter rotor tuning based on neural network and particle swarm optimization[J]. Journal of Beijing University of Aeronautics and Astronautics, 2011, 37(3): 283-288. (in Chinese)
Citation: Liu Hongmei, Lü Chen, Ouyang Pingchao, et al. Helicopter rotor tuning based on neural network and particle swarm optimization[J]. Journal of Beijing University of Aeronautics and Astronautics, 2011, 37(3): 283-288. (in Chinese)

Helicopter rotor tuning based on neural network and particle swarm optimization

  • Received Date: 11 Jan 2010
  • Publish Date: 31 Mar 2011
  • Considering the drawbacks of traditional rotor adjustment method without calculating possible nonlinear between rotor adjustments and fuselage vibration signals of the helicopter, a new rotor adjustment method based on the general regression neural network (GRNN) and the particle swarm optimization (PSO) was presented. GRNN network was employed to model the relationship of the rotor adjustment parameters and the fuselage vibrations, whose input parameters are rotor adjustment parameters and whose outputs are acceleration measurements along the three axes of rotor shaft and the fuselage. With the helicopter vibration as an objective function, the PSO was used to make a global optimization to find the suitable rotor adjustments corresponding to the minimum vibrations. Flight test results indicate that the neural networks are easily updated if new data becomes available thus allowing the system to evolve and mature in the course of its use.

     

  • loading
  • [1] Sam Ventres,Richard E Hayden.Rotor tuning using vibration data only //American Helicopter Society 56th Annual Forum.Virginia:American Helicopter Society,2000:623-629 [2] Wang Shengda,Danai Kourosh,Wilson Mark.Adaptive method of helicopter track and balance[J].Journal of Dynamic Systems,Measurement,and Control,2005,127(2):275-282 [3] Yang Dongzhe,Wang Shengda,Danai Kourosh.Helicopter track and balance by interval modeling //American Helicopter Society 56th Annual Forum.Washington DC:American Helicopter Society,2001:9-11 [4] Wroblewski D,Grabill P,Berry J,et al.Neural network system for helicopter rotor smoothing //Intelligent Automation Corporation.Big Sky,MT:IEEE,2000:271-276 [5] 石喜光,郑立刚,周昊,等.基于广义回归神经网络与遗传算法的煤灰熔点优化[J].浙江大学学报:工学版,2005,39(8):1189-1242 Shi Xiguang,Zheng Ligang,Zhou Hao,et al.Combining general regression neural network and genetic algorithm to optimize ash fusion temperature[J].Journal of Zhejiang University:Engineering Science,2005,39(8):1189-1242(in Chinese) [6] Liao Zhiwei,Ye Qinghua,Wang Gang,et al.Adaptive multi-fault diagnosis of power system based on GRNN[J].Journal of South China University of Technology:Natural Science Edition,2005:33(9):6-9 [7] Farid Melgani,Yakoub Bazi.Classification of electro-cardiogram signals with support vector machines and particle swarm optimization [J].IEEE Transactions on information Technology in Biomedicine,2008,12(5):667-677 [8] Said M Mikki,Ahmed A Kishk.Quantum particle swarm optimization for electromagnetics[J].IEEE Trans-actions on Antennas and Propagation,2006,54(10):2764-2775 [9] Ling S H,Iu H H C,Chan K Y.Hybrid particle swarm optimization with wavelet mutation and its industrial applications [J].IEEE Transactions on Systems,Man,and Cybernetics-PART B:Cybernetics,2008,38(3):743-763 [10] Liu Dasheng,Tan K T,Goh C K.A multi objective memetic algorithm based on particle swarm optimization [J].IEEE Transactions on Systems,Man,and Cybernetics-PART B:Cybernetics,2007,37(1):42-50
  • 加载中

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Article Metrics

    Article views(4505) PDF downloads(984) Cited by()
    Proportional views
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return