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It is still necessary to investigate the detection of structural damage under ambient excitations since the excitations are random and unmeasured while measurement noises are inevitable. In this paper, a method based on the synthesis of cross-correlation functions of partial structural responses and the extended Kalman filter (EKF) approach is proposed for the identification and damage detection of structures under ambient excitations, in which both independent stationary and non-stationary white noise excitations in the product models are discussed. First, the equations of cross-correlation functions of structural responses are established when the ambient excitations are independent stationary white noise processes. Then, the EKF approach is utilized to identify structural parameters and cross-correlation functions using partial measurements of structural acceleration responses. Structural damage is detected based on the degradations of the identified structural element stiffness parameters. Finally, the proposed method is extended to deal with independent non-stationary white noise excitations in the product models. The numerical simulation examples of the ASCE structural health monitoring benchmark building subject to ambient excitation, a moment resisting frame model under white noise excitation, and a cantilever beam model under multiple independent non-stationary excitations are used to validate the feasibility of the proposed method. It is shown that the method is not sensitive to measurement noises. Also, a lab experimental study of the identification of a multi-story shear structure is investigated to further illustrate the applicability of the proposed method. [ABSTRACT FROM AUTHOR]

Under ambient excitation of white noise, structural modal parameters can be identified from cross-power spectrum calculated from structural outputs, without known input. The minimization of difference between theoretical value and test value of cross-power spectrum - the former is an equation including modal parameters to be identified, and the latter is computed based on the output-only data of structure - is adopted as an objective function for optimization. The optimal objective function value can be obtained through optimal modal parameter search. Quantum-behaved particle swarm optimization (QPSO) - swarm intelligence optimization algorithm based on particle swarm optimization (PSO) - is used for optimization to identify the modal parameters of structure under the ambient excitation. Then, the modal parameter identification method based on QPSO presented herein had been demonstrated by a numerical simulation of three-span continuous beam and experimental results of a three story structure. The computed results indicated that QPSO can be effectively used in the structural modal parameter identification under ambient excitation. [ABSTRACT FROM AUTHOR]