Vibration-based monitoring of mechanical structures often involves continuous monitoring that result in high data volume and instrumentation with a large array of sensors. Previously, we have shown that Compressive Sensing (CS)-based vibration monitoring can significantly reduce both volume of data and number of sensors in temporal and spatial domains respectively. In this work, further analysis of CS-based detection and localization of structural changes is presented. Incorporating damping and noise handling in the CS algorithm improved its performance for frequency recovery. CS-based reconstruction of deflection shape of beams with fixed boundary conditions is addressed. Formulation of suitable bases with improved conditioning is explored. Restricting hyperbolic terms to lower frequencies in the basis functions improves reconstruction. An alternative is to generate an augmented basis that combines harmonic and hyperbolic terms. Incorporating known boundary conditions into the CS problem is studied.

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