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基于自然激励技术的颤振边界预测

李扬 周丽 杨秉才

李扬, 周丽, 杨秉才. 基于自然激励技术的颤振边界预测[J]. 航空动力学报, 2016, 31(11): 2744-2749. doi: 10.13224/j.cnki.jasp.2016.11.024
引用本文: 李扬, 周丽, 杨秉才. 基于自然激励技术的颤振边界预测[J]. 航空动力学报, 2016, 31(11): 2744-2749. doi: 10.13224/j.cnki.jasp.2016.11.024
LI Yang, ZHOU Li, YANG Bing-cai. Flutter boundary prediction based on natural excitation technique[J]. Journal of Aerospace Power, 2016, 31(11): 2744-2749. doi: 10.13224/j.cnki.jasp.2016.11.024
Citation: LI Yang, ZHOU Li, YANG Bing-cai. Flutter boundary prediction based on natural excitation technique[J]. Journal of Aerospace Power, 2016, 31(11): 2744-2749. doi: 10.13224/j.cnki.jasp.2016.11.024

基于自然激励技术的颤振边界预测

doi: 10.13224/j.cnki.jasp.2016.11.024
基金项目: 

国家自然科学基金(11172128,51475228);高等学校博士学科点专项科研基金(20123218110001);江苏省普通高校研究生科研创新计划(CXZZ13_0146);江苏高校优势学科建设工程资助项目;机械结构力学及控制国家重点实验室(南京航空航天大学)自主研究课题(0515G01)

详细信息
    作者简介:

    李扬(1989-),男,江苏徐州人,博士生,主要从事颤振信号处理及边界预测研究.

  • 中图分类号: V216.2+4

Flutter boundary prediction based on natural excitation technique

  • 摘要: 为了预测紊流激励条件下机翼的颤振边界,基于自然激励技术提取紊流响应的自由衰减信号,采用矩阵束方法识别模态参数,最后通过Z-W(Zimmerman-Weissenburger)方法计算稳定性判据,拟合判据变化曲线并外推颤振边界.对平板机翼模型进行了数值仿真分析,对单独机翼模型风洞颤振试验数据进行了计算.结果表明:采用自然激励技术与矩阵束方法能够较准确地识别紊流激励响应的模态参数,频率识别误差小于6%,阻尼比识别误差小于30%,结合Z-W方法能够在较低风速较早地预测颤振边界,有助于提高试验的安全性.

     

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出版历程
  • 收稿日期:  2015-03-01
  • 刊出日期:  2016-11-28

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