【摘要】 模态参数识别是结构健康监测与损伤识别技术的基础与核心,准确识别模态参数进而对结构的寿命和安全性做出评价具有非常重要的意义。该文提出了一种新颖的结构模态参数识别方法-首先将信号经过频带滤波的预处理,然后进行EMD(经验模态分解)过程,利用相关系数来判定真正的IMF(本征模函数),最后利用NExT/ARMA相结合的方法来识别出结构的频率和阻尼比。模态试验验证了所提方法的可行性和有效性,并将它与HHT、NExT/ARMA方法进行了比较。研究表明,所提方法具有很好的适应性,可以比较准确地识别出结构的频率和阻尼比。更多还原

【Abstract】 Modal parameter identification is the core and key of structural health monitoring and damage detection,which is crucial to evaluate the life and safety of a structure.This paper proposes a novel method for modal parameter identification.At first,the response signal is pre-processed by the band-pass filter,and then a series of Intrinsic Mode Functions(IMFs) are separated using the Empirical Mode Decomposition(EMD) from the measured response signals.Next the real IMF is determined by the correlative coefficient between the separated IMF and the measured signal.Finally,the Natural Excitation Technique(NExT) and ARMA model are combined to identify structural modal parameters as soon as the real IMF is obtained.The presented method is applied to identify modal parameters of a 7-storey framed-structure.The identification results are compared with those of other identification methods,namely HHT and NExT/ARMA.This research shows that the approach proposed can extract modal parameters effectively,and also has excellent adaptability.更多还原