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Vibration-based structural performance assessment via output-only sub-Nyquist/compressive wireless sensor data

Gkoktsi, K., Giaralis, A. ORCID: 0000-0002-2952-1171, Klis, R. , Dertimanis, V. & Chatzi, E. (2017). Vibration-based structural performance assessment via output-only sub-Nyquist/compressive wireless sensor data. Paper presented at the 4th Conference on Smart Monitoring, Assessment and Rehabilitation of Civil Structures- SMAR 2017, 13 - 15 September 2017, Zurich, Switzerland.

Abstract

This paper assesses two different approaches for efficient output - only Vibration - based Structural Health Monitoring (V - SHM) in large - scale civil engineering structures, promoting the use of dense arrays of low - power wireless sensors. Firstly, a non - uniform deterministic sub - Nyquist multi - coset sampling scheme is considered to acquire ambient stationary structural response signals. This sampling scheme is coupled with a power spectrum blind sampling technique along with the frequency domain decomposition algorithm of operational modal analysis to obtain structural modal properties. This is accomplished without necessitating either signal reconstruction in the time - domain or signal sparsity assumption . Secondly, a spectro-temporal compressive sensing approach is considered applicable to cases where sign al reconstruction in time - domain is desired. The latter approach considers non-uniform in time random sampling at sub - Nyquist average rates informed by prior knowledge of signal sparsity gained through smart on-sensor operations and sensor/server communication. The usefulness and applicability of two approaches is numerically demonstrated by considering field recorded data pertaining to the monitoring of an overpass open to the traffic and of an operating on-shore wind turbine .

Publication Type: Conference or Workshop Item (Paper)
Additional Information: Gkoktsi, K., Giaralis, A, Klis, Roman, Dertimanis, Vasilios & Chatzi, Eleni (2017). Vibration-based structural performance assessment via output-only sub-Nyquist/compressive wireless sensor data. Paper presented at the 4th Conference on Smart Monitoring, Assessment and Rehabilitation of Civil Structures- SMAR 2017, 13 - 15 September 2017, Zurich, Switzerland. http://www.smar2017.org/
Departments: School of Science & Technology > Engineering
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