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Modified Cross-Correlation Method for the Blind Identification of Structures
Authors:B Hazra  A J Roffel  S Narasimhan  M D Pandey
Affiliation:1Graduate Research Assistant, Dept. of Civil and Environmental Engineering, Univ. of Waterloo, Waterloo, ON, Canada N2L 3G1.
2Assistant Professor, Dept. of Civil and Environmental Engineering, Univ. of Waterloo, 200 University Ave. W., Waterloo, ON, Canada N2L 3G1 (corresponding author). E-mail: snarasim@uwaterloo.ca
3Professor, Dept. of Civil and Environmental Engineering, Univ. of Waterloo, Waterloo, ON, Canada N2L 3G1.
Abstract:Recently, blind source separation (BSS) methods have gained significant attention in the area of signal processing. Independent component analysis (ICA) and second-order blind identification (SOBI) are two popular BSS methods that have been applied to modal identification of mechanical and structural systems. Published results by several researchers have shown that ICA performs satisfactorily for systems with very low levels of structural damping, for example, for damping ratios of the order of 1% critical. For practical structural applications with higher levels of damping, methods based on SOBI have shown significant improvement over ICA methods. However, traditional SOBI methods suffer when nonstationary sources are present, such as those that occur during earthquakes and other transient excitations. In this paper, a new technique based on SOBI, called the modified cross-correlation method, is proposed to address these shortcomings. The conditions in which the problem of structural system identification can be posed as a BSS problem is also discussed. The results of simulation described in terms of identified natural frequencies, mode shapes, and damping ratios are presented for the cases of synthetic wind and recorded earthquake excitations. The results of identification show that the proposed method achieves better performance over traditional ICA and SOBI methods. Both experimental and large-scale structural simulation results are included to demonstrate the applicability of the newly proposed method to structural identification problems.
Keywords:Vibration  Monitoring  Identification  Correlation  Signal processing  
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