航空学报 > 2020, Vol. 41 Issue (7): 223548-223548   doi: 10.7527/S1000-6893.2020.23548

基于加速度频响函数小波分解的模型修正方法

彭珍瑞, 曹明明, 刘满东   

  1. 兰州交通大学 机电工程学院, 兰州 730070
  • 收稿日期:2019-10-08 修回日期:2019-12-23 出版日期:2020-07-15 发布日期:2020-02-13
  • 通讯作者: 彭珍瑞 E-mail:pengzr@mail.lzjtu.cn
  • 基金资助:
    国家自然科学基金(51768035);甘肃省高校协同创新团队项目(2018C-12);兰州市人才创新创业项目(2017-RC-66);兰州交通大学"百名青年优秀人才培养计划"(152022)

Model updating method based on wavelet decomposition of acceleration frequency response function

PENG Zhenrui, CAO Mingming, LIU Mandong   

  1. School of Mechanical Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China
  • Received:2019-10-08 Revised:2019-12-23 Online:2020-07-15 Published:2020-02-13
  • Supported by:
    National Natural Science Foundation of China (51768035); Collaborative Innovation Team Project of Universities in Gansu Province (2018C-12); Talent Project of Lanzhou City (2017-RC-66); Foundation of A Hundred Youth Talents Training Program of Lanzhou Jiaotong University (152022)

摘要: 为提高模型修正效率,满足修正方法对于实测环境噪声的鲁棒性,将Kriging模型和小波分解引入加速度频响函数模型修正。首先,将加速度频响函数进行小波分解,用得到的第1层幅值较大的小波系数来表征原频响函数。其次,采用拉丁超立方抽样对初选待修正参数进行设计,根据设计结果对各参数进行灵敏度分析,从而确定模型修正的待修正参数,以待修正参数作为Kriging模型输入,所对应的小波系数作为Kriging模型输出,通过混合灰狼算法寻得最优Kriging模型相关系数,建立精确有效的Kriging模型。最后,以目标加速度频响函数小波分解的小波系数与Kriging模型输出的小波系数差值最小为目标,通过水循环算法求解模型待修正参数。数值算例表明,所提模型修正方法具有良好的修正效果,即使在加速度频响函数中加入信噪比为5 dB的高斯白噪声时,修正误差也低于4%,证明了该方法对于随机噪声的鲁棒性。

关键词: 模型修正, Kriging模型, 加速度频响函数, 小波分解, 相关系数

Abstract: To improve the efficiency of model updating and satisfy its robustness for the measured environmental noise, the Kriging model and wavelet decomposition are introduced into the model updating of the acceleration frequency response function. Firstly, the acceleration frequency response function is decomposed by wavelets, and the obtained wavelet coefficients with large amplitudes in the first layer are used to represent the original frequency response function. Secondly, the Latin hypercube sampling is utilized to design the primary parameters to b