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Proceedings Paper

System identification of a tied arch bridge using reference-based wireless sensor networks
Author(s): Colby Hietbrink; Matthew J. Whelan
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Paper Abstract

Vibration-based methods of structural health monitoring are generally founded on the principle that localized damage to a structure would exhibit changes within the global dynamic response. Upon this basis, accelerometers provide a unique health monitoring strategy in that a distributed network of sensors provides the technical feasibility to isolate the onset of damage without requiring that any sensor be located exactly on or in close proximity to the damage. While in theory this may be sufficient, practical experience has shown significant improvement in the application of damage diagnostic routines when mode shapes characterized by strongly localized behavior of specific elements are captured by the instrumentation array. In traditional applications, this presents a challenge since the cost and complexity of cable-based systems often effectively limits the number of instrumented locations thereby constraining the modal parameter extraction to only global modal responses. The advent of the low-cost RF chip transceiver with wireless networking capabilities has afforded a means by which a substantial number of output locations can be measured through referencebased testing using large-scale wireless sensor networks. In the current study, this approach was applied to the Prairie du Chien Bridge over the Mississippi River to extract operational mode shapes with high spatial reconstruction, including strongly localized modes. The tied arch bridge was instrumented at over 230 locations with single-axis accelerometers conditioned and acquired over a high-rate lossless wireless sensor network with simultaneous sampling capabilities. Acquisition of the dynamic response of the web plates of the arch rib was specifically targeted within the instrumentation array for diagnostic purposes. Reference-based operational modal analysis of the full structure through data-driven stochastic subspace identification is presented alongside finite element analysis results for confirmation of modal parameter plausibility. Particular emphasis is placed on the identification and reconstruction of modal response with large contribution from the arch rib web plates.

Paper Details

Date Published: 30 March 2012
PDF: 14 pages
Proc. SPIE 8346, Smart Sensor Phenomena, Technology, Networks, and Systems Integration 2012, 83460W (30 March 2012); doi: 10.1117/12.915398
Show Author Affiliations
Colby Hietbrink, The Univ. of North Carolina at Charlotte (United States)
Matthew J. Whelan, The Univ. of North Carolina at Charlotte (United States)


Published in SPIE Proceedings Vol. 8346:
Smart Sensor Phenomena, Technology, Networks, and Systems Integration 2012
Theodore E. Matikas, Editor(s)

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