Most structural responses can be considered as the superposition of some monotonic components. These monotonic components contain modal information that can be used for structural damage detection and health monitoring. This paper presents a comparative study of three techniques for signal decomposition and analysis. These techniques are the wavelet transform (WT) technique, the empirical mode decomposition (EMD) technique, and the principle component analysis (PCA) technique. These techniques are all capable of decomposing multi-component signals into a summation of mono-components without resorting to the traditional frequency-domain approach. All three techniques can estimate natural frequencies, damping ratios and mode shapes of a structure from its time-domain vibration responses and hence can be used to monitor structural condition. A numerical study on a three-story shear-beam building frame is performed and presented to show the accuracy of these techniques.
A novel structural damage assessment technique based on the principal component analysis (PCA) and the flexibility matrix approach is proposed in this paper. The technique is a model free method and can be used for detecting damage occurrence and location. The PCA is adopted firstly to decompose a set of correlated structural response measurements into statistically uncorrelated ones. Under the condition of small damping, these uncorrelated data can be shown to be related to modal responses and can be used to estimate the modal properties of a structure. The structural flexibility matrix can then be constructed using the estimated modal parameters. The change in the flexibility matrix gives an indication of the occurrence and location of structural damage. A numerical study on a 7-storey shear beam building model is performed to illustrate the applicability of the proposed technique. The results show that the proposed technique can accurately identify the occurrence and location of structural damage when the building is subjected to various earthquake excitations.