Condition assessment of structure with tuned mass damper using empirical wavelet transform

Tuned mass damper (TMD) has been one of the most commonly used passive vibration control devices over the past few decades. While an optimally designed TMD can significantly suppress the structural vibration, detuning often occurs due to various reasons such as change in operating conditions or variation in primary structure properties, resulting in degradation of TMD's performance. In order to restore its performance, it is necessary to estimate the modal properties of the primary structure, and perform the re-tuning process. Such an exercise requires powerful signal processing methods to successfully extract the structural modes in the presence of closely-spaced modes. This study focuses on the identification of modal frequencies and damping of the structure installed with a TMD. In view of the advantages and limitations of existing modal identification methods, this paper provides a new technique that combines the second-order blind identification (SOBI) method with the empirical wavelet transform (EWT) to delineate closely-spaced frequencies. While the SOBI method does not guarantee the separation of closely-spaced modes and suffers from the limitation of generating mode-mixed modal responses, the EWT operates on the modal responses estimated by the SOBI and yields the closely-spaced natural frequencies. The proposed method is illustrated using a six-story simulation model with a wide range of detuning cases. An experiment on a three-story bench-scale model equipped with a TMD is also conducted to validate the applicability of the proposed method.