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Smart Structures and Systems
  Volume 11, Number 1, January 2013, pages 123-134

Structural modal identification through ensemble empirical modal decomposition
J. Zhang, R.Q. Yan and C.Q. Yang

    Identifying structural modal parameters, especially those modes within high frequency range, from ambient data is still a challenging problem due to various kinds of uncertainty involved in vibration measurements. A procedure applying an ensemble empirical mode decomposition (EEMD) method is proposed for accurate and robust structural modal identification. In the proposed method, the EEMD process is first implemented to decompose the original ambient data to a set of intrinsic mode functions (IMFs), which are zero-mean time series with energy in narrow frequency bands. Subsequently, a Sub-PolyMAX method is performed in narrow frequency bands by using IMFs as primary data for structural modal identification. The merit of the proposed method is that it performs structural identification in narrow frequency bands (take IMFs as primary data), unlike the traditional method in the whole frequency space (take original measurements as primary data), thus it produces more accurate identification results. A numerical example and a multiple-span continuous steel bridge have been investigated to verify the effectiveness of the proposed method.
Key Words
    empirical mode decomposition; modal identification; signal processing; narrow frequency bands
J. Zhang : Key Laboratory of C&PC Structures of the Ministry of Education, Southeast University, Nanjing 210096, China ,
International Institute for Urban Systems Engineering, Southeast University, Nanjing 210096, China
R.Q. Yan : School of Instrument Science and Engineering, Southeast University, Nanjing 210096, China
C.Q. Yang :International Institute for Urban Systems Engineering, Southeast University, Nanjing 210096, China

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