Improved Automatic Operational Modal Analysis Method and Application to Large-Scale Bridges

Abstract How to identify modal parameters accurately and automatically is an important issue in structural health monitoring. In this paper, two aspects of this issue are investigated based on the algorithm of natural excitation technology (NExT) in conjunction with the Eigensystem realization algorithm (ERA): (1) First, the selection of the user-defined parameters (sampling points of the fast Fourier transform and the data length) is discussed. Based on this, an empirical equation for determining the dimensions of the Hankel matrix is presented; (2) Second, we propose an improved stabilization diagram to determine the physical modes automatically. The modal frequency, damping ratio, extended modal amplitude coherence (EMAC) and modal amplitude coherence (MAC) are applied as criteria. The reliability of the proposed method is verified by a numerical simulation and two applications to a large-scale bridge. It is shown that the proposed method can distinguish the physical modes from spurious modes effectively and the most reliable physical modes can be automatically identified.