Fast Bayesian Ambient Modal Identification Incorporating Multiple Setups

Abstract

In full-scale ambient vibration tests, many situations exist where it is required to obtain a detailed mode shape of a structure with a limited number of sensors. A common feasible strategy is to perform multiple setups with each one covering a different part of the structure while sharing some reference degrees of freedom (DOF) in common. Methods exist that assemble the mode shapes identified in individual setups to form a global one covering all measured DOF. This paper presents a fast Bayesian method for modal identification capable of incorporating the fast Fourier transform information in different setups consistent with probability logic. The method allows the global mode shape to be determined, taking into account the quality of data in different setups. A fast iterative algorithm is developed that allows practical implementation even for a large number of DOF. The method is illustrated with synthetic and field test data. Challenges of the mode shape assembly problem arising in field applications are investigated through a critical appraisal.