Abstract
Singular spectrum analysis (SSA) is a novel technique and has proven to be a powerful tool for time series data analysis. Through singular value decomposition of Hankel matrix data, the time series of data can be decomposed into several simple, independent and identifiable components from singular values and singular vectors. It has already been widely applied to process climatic, meteorological, geophysical and economic data. In this paper, we demonstrate that the coupling degree of the 1st and 2nd singular values in SSA contains useful indications on the feature and composition of the analysed signal. The proposed method is successfully applied to the monitoring of structure, such as damage detection of the simulated dynamic system, experimental steel frame, bridge foundation scouring and pier settlement in the laboratory and on-site bridge monitoring during typhoon strike. The proposed algorithm is simple and suitable for structural health monitoring in the field.
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