Long-term Field Monitoring of Fatigue Cracks for Steel Bridges with Wireless Large-Area Strain Sensors
Author
Taher, S.A.Li, J.
Jeong, J.-H.
Laflamme, S.
Jo, H.
Bennett, C.
Collins, W.
Liu, H.
Downey, A.
Shaheen, M.
Affiliation
Department of Civil, Architectural Engineering and Mechanics, University of ArizonaIssue Date
2022Keywords
fatigue crack monitoringlarge-area strain sensor
peak detection
soft elastomeric capacitor
steel bridges
structural health monitoring
traffic loads
wavelet transform
wireless sensors
Metadata
Show full item recordPublisher
SPIECitation
Taher, S. A., Li, J., Jeong, J.-H., Laflamme, S., Jo, H., Bennett, C., Collins, W., Liu, H., Downey, A., & Shaheen, M. (2022). Long-term Field Monitoring of Fatigue Cracks for Steel Bridges with Wireless Large-Area Strain Sensors. Proceedings of SPIE - The International Society for Optical Engineering, 12046.Rights
Copyright © 2022 SPIE.Collection Information
This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.Abstract
Steel bridges are susceptible to fatigue damage under traffic loading and many bridges operate with existing cracks. The discovery and long-term monitoring of those fatigue cracks are critical for safety evaluations. In previous studies, the ability of the soft elastomeric capacitor (SEC) sensor that measures large-area strain was validated for detecting and monitoring fatigue crack growth in a laboratory environment. In this study, the performance of the technology is evaluated for field applications, for which an approach for long-term monitoring of fatigue cracks is developed. The approach consists of an integrated system, termed the Wireless Large-Area Strain Sensors (WLASS), for wireless data collection and storage, and an algorithm for monitoring fatigue cracks with bridge response induced by traffic loading. In particular, the WLASS consists of soft elastomeric capacitors (SECs) combined with sensor boards to convert capacitance to a measurable change in voltage and a wireless sensing platform equipped with event-triggered sensing, wireless data collection, cloud storage, and remote data retrieval. A modified crack growth index (CGI) is developed through wavelet transform. Using the measurements from the integrated system, the modified CGI is able to obtain the crack status under impulsive loading events due to traffic. The performance of the developed approach is validated using a steel highway bridge. © 2022 SPIE.Note
Immediate accessISSN
0277-786XISBN
9781510649675Version
Final published versionae974a485f413a2113503eed53cd6c53
10.1117/12.2613072