Abstract
The present study aims to demonstrate the capabilities of singular spectrum analysis (SSA) as a filter bank that could potentially be integrated into a modal identification framework using single-sensor output information. SSA reconstructs the original time series using principal components from the signal subspace—thereby eliminating noise components altogether—and yields a filtered signal that finds its use in modal identification. Using time-domain decomposition and least-squares technique, the modal response generated using SSA is fit with a free-decay signal from which the estimates of natural frequencies and damping ratios are carried out. The paper attempts to investigate a simple model of a dynamical system and analyzes it using the proposed approach to provide a comparison with traditional operational modal analysis techniques. The results demonstrate that SSA can be used as a powerful tool for the analysis of vibratory behavior for structures exhibiting well-separated spectral components. Inherent filtering embedded within its framework and its seamless integration into a modal identification framework hold strong promise for application inbuilt infrastructure systems.
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Bhowmik, B. (2023). Improved Single-Sensor-Based Modal Identification Using Singular Spectrum Analysis. In: Nandagiri, L., Narasimhan, M.C., Marathe, S. (eds) Recent Advances in Civil Engineering. CTCS 2021. Lecture Notes in Civil Engineering, vol 256. Springer, Singapore. https://doi.org/10.1007/978-981-19-1862-9_56
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DOI: https://doi.org/10.1007/978-981-19-1862-9_56
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