A hybrid output-only scheme for precise modal estimation and uncertainty quantification of large-scale structure through vibration-based measurements

Abstract

In structural health monitoring or operational modal analysis, owing to unknown or unmeasured ambient excitation information, only structural responses are typically available for modal identification. In this context, bias and variance (uncertainty) errors inevitably exist in modal estimates (especially damping estimates), resulting in inaccurate determinations of structural dynamic properties. To this end, a hybrid output-only scheme based on the second-order blind identification, block bootstrap, and enhanced covariance-driven stochastic subspace identification algorithm with first-order perturbation is presented in this paper to perform precise modal estimation and uncertainty quantification. The accuracy and effectiveness of the hybrid scheme in performing modal identification are verified by numerical simulation study of a framework structure. Furthermore, the hybrid method is applied to analyze recorded acceleration responses of a supertall building with 600 m height during Typhoon Kompasu by considering different sensor setups to verify its applicability and robustness in practical applications, and further investigates the dynamic properties of the skyscraper and their variations during the typhoon. The numerical simulation and field measurement studies demonstrate that the hybrid scheme can effectively reduce the bias errors and quantify the variance errors in modal estimates through a single ambient vibration test, thereby improving the confidence and accuracy of modal identification. Notably, the hybrid method is an effective tool to perform high-accuracy modal estimation and uncertainty quantification for large-scale structures under ambient excitations.