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摘要: 针对直升机旋翼系统非线性、难以建模的特点,采用径向基函数(RBF,Radial Basis Function)神经网络建立直升机旋翼动平衡调整模型.根据约束条件以直升机机身振动值作为目标函数建立适应度函数,以旋翼系统的调整参数为优化变量,进行神经网络学习和优化.利用粒子群优化(PSO,Particle Swarm Optimization)算法对适应度函数进行寻优,获得当直升机振动最小时的桨叶的调整参数.实验结果表明:PSO算法寻优效率方面高于遗传算法;RBF神经网络和PSO算法相结合可以有效地实现直升机旋翼动平衡调整.Abstract: Considering characteristics of non-linear and difficult to model for the rotor system, helicopter rotor dynamic balancing adjustment models was established by radial basis function(RBF)neural network. According to the constraints, the fitness function was established by using the helicopter vibration as objective function and the optimization variables were used by the adjustment parameters of rotor. The radial basis function neural network learning and optimization were used by the helicopter vibration and the adjustment parameters of rotor. Particle swarm optimization(PSO) algorithm was used to make a global optimization to find the suitable rotor adjustments corresponding to the minimum vibrations. The experimental results indicate that the particle swarm optimization algorithm is higher than the genetic algorithm in the aspect of efficiency optimization and the radial basis function combined with the particle swarm optimization algorithm can effectively achieve the helicopter rotor dynamic balance adjustment.
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Key words:
- rotor /
- radial basis function /
- particle swarm optimization /
- optimization
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[1] 薛伟松,邢士喜,郑牧,等.直升机旋翼锥体及动平衡设备校验系统的研究[J].测控技术，2006，25(3):4-7 Xue Weisong，Xing Shixi，Zheng Mu，et al.Research on checkout system for trackheight and dynamic balance equipment of helicopter[J].Testing and Control Technology，2006，25(3):4-7 (in Chinese) [2] Ventres Sam，Hayden Richard E.Rotor tuning using vibration data only[C]//American Helicopter Society 56th Forum.Alexandria:American Helicopter Society，2000:623-629 [3] Wang Shengda，Danai Kourosh，Wilson Mark.Adaptive method of helicopter track and balance[J].Journal of Dynamic Systems，Measurement，and Control,2005，127(6):275-282 [4] 袁海文,吕弘,袁海斌.基于RBF神经网络的控制电器元件故障诊断[J].北京航空航天大学学报,2006,32(5):544 547 Yuan Haiwen，Lü Hong，Yuan Haibin.Fault diagnosis of control electric component based on RBF neural network[J].Journal of Beijing University of Aeronautics and Astronautics,2006,32(5):544-547(in Chinese) [5] Liu Hongmei,Wang Shaoping,Ouyang Pingchao.Fault diagnosis in a hydraulic position servo system using RBF neural network[J].Chinese Journal of Aeronautics,2006,19(4):346-353 [6] 李炳宇，萧蕴诗，江镭.PSO算法在工程优化问题中的应用[J].计算机工程与应用,2004(18):74-76 Li Bingyu，Xiao Yunshi，Jiang Lei.Application of particle swarm optimization in engineering optimization problem[J].Computer Engineering and Applications,2004(18):74-76(in Chinese) [7] 乔维德.基于改进粒子群算法神经网络的电力电子电路故障诊断[J].电气传动自动化，2008,30(5):29-31 Qiao Weide.Fault diagnosis of power electronic circuits based on improved PSO algorithm neural network[J].Electric Drive Automation,2008,30(5):29-31(in Chinese) -
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