• CN:11-2187/TH
  • ISSN:0577-6686

›› 2009, Vol. 45 ›› Issue (9): 31-35.

• 论文 • 上一篇    下一篇

大功率船用齿轮箱系统耦合非线性动态特性研究

朱才朝;陆波;宋朝省;徐向阳   

  1. 重庆大学机械传动国家重点实验室;西南科技大学制造科学与工程学院
  • 发布日期:2009-09-15

Research on Nonlinear Coupling Dynamic Characteristics of Large Burden Marine Gearbox

ZHU Caichao;LU Bo;SONG Chaosheng;XU Xiangyang   

  1. The State Key Laboratory of Mechanical Transmission, Chongqing University College of Manufacturing Science and Engineering, Southwest University of Science and Technology
  • Published:2009-09-15

摘要: 为揭示虚拟仿真环境下的齿轮系统非线性振动的内在规则性,将某大型重载船用齿轮箱系统分为传动子系统和结构子系统,通过轴承把两个子系统耦合起来,建立齿轮—轴—轴承—箱体耦合系统非线性有限元模型。在考虑传动子系统内部激励和外部激励的影响下,对系统动态特性进行了数值仿真。分析了时间历程曲线、功率谱密度、相轨迹、庞加莱截面,计算了最大Lyapunov指数,得出该大型船用齿轮箱在工作负载下,系统运动为周期性运动,不存在混沌现象;对振动信号做进一步预测,非线性动力学方法预测结果与有限元计算结果吻合较好,研究表明采用两者相结合的方法,能够准确地预估齿轮动态响应,揭示振动信号的内在规律,为齿轮系统动态设计提供参考依据。

关键词: 船用齿轮箱, 非线性动力学, 混沌识别, 耦合振动, 预测

Abstract: The main objective of this research is to reveal the intrinsic principle of nonlinear vibration of gear system in virtual simulative environment. A nonlinear finite element model of a gear-rotor-bearing-box coupling system is developed by coupling transmission subsystem and structure subsystem of a large-scale burden marine gearbox with the support of bearing. By the simulation of its kinetic characteristic under the effect of internal and external excitations on the transmission subsystem, the time history plot, power spectrum density, phase trace and Poincare section are analyzed, and the maximum Lyapunov exponent is calculated. The results reveal that the system operates periodically and chaos phenomena do not occur under the current operating load. The further prediction of vibration signal shows that the prediction results by nonlinear dynamics methods and the results of finite element calculation coincide well, and indicates that the combination of the two methods can accurately predict the dynamic response of gears and reveal the inherent law of vibration signal, thus providing a scientific basis for the dynamic design of gear system.

Key words: Chaos identification, Coupling vibration, Forecasting, Marine gearbox, Nonlinear dynamics

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