摘要
基于工程结构振动信号的分析与处理识别结构的模态参数,是结构健康监测和损伤诊断的重要手段之一。基于傅里叶分析的信号处理方法对非线性、非稳态信号的处理能力差,传统的模态参数识别方法也存在阻尼比识别精度不高的问题。基于Hilbert-Huang变换和自然激励技术,提出了一种新的模态参数识别方法,首先通过经验模态分解和Hilbert变换提取信号的瞬时特性,进而利用自然激励技术和模态分析的基本理论识别结构的模态频率和模态阻尼比。利用这一方法,对12层钢筋混凝土框架模型振动台试验一测点的加速度记录进行了处理,识别了模态参数,识别结果与其它识别方法及有限元分析结果的对比表明该方法识别模态频率是可靠的,而模态阻尼比的识别虽然较传统的基于傅里叶变换的半功率带宽法有所改进,但识别的精准性仍然难以确认。
Identifying modal parameters via processing vibration signals is one of the mainstream approaches for structural health monitoring and damage diagnosis. The processing approaches based on Fourier analysis are not able to process nonlinear and non-stationary signals. In addition, most of traditional identification methods suffer from low precision to identify damping. Therefore, a new approach is proposed for identifying modal parameters based on Hilbert-Huang transform （HHT） and natural excitation technique （NExT）. First, the instantaneous characteristics of the original signal are extracted by means of empirical mode decomposition （EMD） and Hilbert transform （HT）. Then, NExT and basic modal analysis theory are used to identify modal frequencies and modal damping ratios. Furthermore, the original acceleration record from the shaking table test of a 12-storey RC frame model is processed and modal parameters are identified by the proposed approach. And identification results are compared with the results from other identification algorithms and finite element analysis.Comparison indicates that the proposed approach is reliable to identify modal frequencies. Although identification of modal damping ratios gets improved by comparison with half-power bandwidth method, it is still difficult to confirm the precision of the results.
出处
《工程力学》
EI
CSCD
北大核心
2010年第8期54-59,共6页
Engineering Mechanics
基金
甘肃省科技攻关项目(2GS057-A52-008)
