Synchrosqueezed wavelet transform-fractality model for locating, detecting, and quantifying damage in smart highrise building structures

Abstract

A new methodology is presented for (a) detecting, (b) locating, and (c) quantifying the damage severity in a smart highrise building structure. The methodology consists of three steps: In step 1, the synchrosqueezed wavelet transform is used to eliminate the noise in the signals. In step 2, a nonlinear dynamics measure based on the chaos theory, fractality dimension (FD), is employed to detect features to be used for damage detection. In step 3, a new structural damage index, based on the estimated FD values, is proposed as a measure of the condition of the structure. Further, the damage location is obtained using the changes of the estimated FD values. Three different FD algorithms for computing the fractality of time series signals are investigated. They are Katz's FD, Higuchi's FD, and box dimension. The usefulness and effectiveness of the proposed methodology are validated using the sensed data obtained experimentally for the 1:20 scaled model of a 38-storey concrete building structure.