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A sub-Nyquist co-prime sampling music spectral approach for natural frequency identification of white-noise excited structures

Gkoktsi, K. & Giaralis, A. ORCID: 0000-0002-2952-1171 (2018). A sub-Nyquist co-prime sampling music spectral approach for natural frequency identification of white-noise excited structures. In: Proceedings of the 8th International Conference on Computational Stochastic Mechanics (CSM 8).


Motivated by practical needs to reduce data transmission payloads in wireless sensors for vibration-based monitoring of civil engineering structures, this paper proposes a novel approach for identifying resonant frequencies of white-noise excited structures using acceleration measurements acquired at rates significantly below the Nyquist rate. The approach adopts the deterministic co-prime sub-Nyquist sampling scheme, originally developed to facilitate telecommunication applications, to estimate the autocorrelation function of response acceleration time-histories of low-amplitude white-noise excited structures treated as realizations of a stationary stochastic process. This is achieved without posing any sparsity conditions to the signals. Next, the standard MUSIC algorithm is applied to the estimated autocorrelation function to derive a denoised super-resolution pseudo-spectrum in which natural frequencies are marked by prominent spikes. The accuracy and applicability of the proposed approach is numerically assessed using computer-generated noise-corrupted acceleration time-history data obtained by a simulation-based framework pertaining to a white-noise excited structural system with two closely-spaced modes of vibration carrying the same amount of energy, and a third isolated weakly excited vibrating mode. All three natural frequencies are accurately identified by sampling at as low as 78% below Nyquist rate for signal to noise ratio as low as 0dB (i.e., energy of additive white noise equal to the signal energy), suggesting that the proposed approach is robust and noise-immune while it can reduce data transmission requirements in acceleration wireless sensors for natural frequency identification of engineering structures.

Publication Type: Conference or Workshop Item (Paper)
Additional Information: Copyright © 2019 CSM8 Editors. All rights reserved.
Publisher Keywords: Co-prime sampling, MUSIC pseudo-spectrum, compressive sensing, spectral estimation, system identification, closely-spaced modes
Subjects: T Technology > TA Engineering (General). Civil engineering (General)
Departments: School of Science & Technology > Engineering
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