吴继忠, 花向红, 高俊强. 基于小波包分解的结构自振特征提取及多路径误差分离[J]. 武汉大学学报 ( 信息科学版), 2010, 35(4): 486-490.
引用本文: 吴继忠, 花向红, 高俊强. 基于小波包分解的结构自振特征提取及多路径误差分离[J]. 武汉大学学报 ( 信息科学版), 2010, 35(4): 486-490.
WU Jizhong, HUA Xianghong, GAO Junqiang. Feature Extraction of Structure Natural Vibration and Multipath Separation Based on Wavelet Packet Decomposition[J]. Geomatics and Information Science of Wuhan University, 2010, 35(4): 486-490.
Citation: WU Jizhong, HUA Xianghong, GAO Junqiang. Feature Extraction of Structure Natural Vibration and Multipath Separation Based on Wavelet Packet Decomposition[J]. Geomatics and Information Science of Wuhan University, 2010, 35(4): 486-490.

基于小波包分解的结构自振特征提取及多路径误差分离

Feature Extraction of Structure Natural Vibration and Multipath Separation Based on Wavelet Packet Decomposition

  • 摘要: 为了准确获取结构自振特性,通过分析多路径误差和结构振动的频率特征,采用小波包分解和频谱分析相结合的方法,在不同尺度下进行特定成分的提取,再作频率特性分析。实验结果表明,小波包能够有效地分离多路径误差,实现结构振动特征的提取,GPS测定的结构自振频率与理论值吻合较好,并且具有很好的稳定性。

     

    Abstract: Multipath is the dominant error source in the structural vibration monitoring using GPS. In order to obtain the characteristics of structure natural vibration accurately, both the frequency characteristics of the multipath and the structural vibration are analyzed, then wavelet packet decomposition is employed to extract specifical components in different scales and spectral analysis is adopted for frequency characteristic analysis. Experimental results show that the wavelet packet can be used to separate multipah error and extract the vibration feature effectively. In addition, the actual vibration frequency obtained using GPS conforms its theoretical value and it has high stability.

     

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