希尔伯特-黄变换
希尔伯特谱分析
情态动词
S变换
希尔伯特变换
小波变换
小波
谐波小波变换
傅里叶变换
模态试验
常数Q变换
振动
模态分析
数学
算法
计算机科学
声学
离散小波变换
数学分析
光谱密度
人工智能
电信
物理
白噪声
材料科学
高分子化学
作者
Shiqiang Qin,Jian Tang,Jiacheng Feng,Yunlai Zhou,Fei Yang,Magd Abdel Wahab
标识
DOI:10.1177/10775463231166428
摘要
To overcome the inaccurate frequency band division in empirical wavelet transform (EWT) induced by high noise and modulation edge band, this study proposes an improved EWT (IEWT) and applies it to operational modal analysis (OMA) in civil structures. The IEWT segments the frequency band using spectral trend determined with removing the high-frequency components of the Fourier spectrum. The synchroextracting transform is employed to denoise the frequency components obtained from IEWT combined with the random decrement technique and Hilbert transform to identify modal parameters. The effectiveness of IEWT and the proposed modal analysis method is comprehensively verified by a full-scale cable-stayed footbridge. The results demonstrate that the proposed IEWT, random decrement technique, and Hilbert transform can accurately identify the modal parameters from multi-setup ambient vibration measurements.
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