TY - CONF
T1 - Evaluation of error of deformed shape determined from strain measurements and double integration of curvature
AU - Sigurdardottir, Dorotea H.
AU - Glisic, Branko
N1 - Funding Information:
This project was supported by the USDOT-RITA DTRT12-G-UTC16 and NSF CMMI-1362723. Any opinions, findings, and conclusions or recommendations expressed herein are those of the authors and do not necessarily reflect the views of the funding agencies. Thanks to Joseph Vocaturo, Michael Littman, Kaitlyn Kliewer, and Dennis Smith for their help with the laboratory experiments.
Funding Information:
This project was supported by the USDOT-RITA DTRT12-G-UTC16 and NSF CMMI-1362723. Any opinions, findings, and conclusions or recommendations expressed herein are those of the authors and do not necessarily reflect the views of the funding agencies. Thanks to Joseph Vocaturo, Michael Littman, Kaitlyn Kliewer, and Dennis Smith for their help with the laboratory experiments. The Streicker Bridge project has been realized with great help, and kind collaboration of several professionals and companies. We would like to thank Steve Hancock and Turner Construction Company; Ryan Woodward and Ted Zoli, HNTB Corporation; Dong Lee and A.G. Construction Corporation; Steven Mancini and Timothy R. Wintermute, Vollers Excavating and Construction, Inc.; SMARTEC SA, Switzerland; Micron Optics, Inc., Atlanta, GA.; Geoffrey Gettelfinger; James P. Wallace; Miles Hersey; Paul Prucnal; Yanhua Deng; Mable Fok; Albert Pearson; Jim Muller; Thomas Thomas; Pepper Vareha; and Faculty and staff of the Department of Civil and Environmental Engineering. The following students installed the sensors on Streicker Bridge: Chienchuan Chen, Jeremy Chen, Jessica Hsu, George Lederman, Kenneth Liew, Maryanne Wachter, Allison Halpern, David Hubbell, Morgan Neal, Daniel Reynolds, and Daniel Schiffner. Hiba Abdel-Jaber, Matthew Horner, Kaitlyn Kliewer, Xi Li, Shue-Thing Ellen Tung, and Yao Yao helped with the test of Streicker Bridge.
Publisher Copyright:
© 2018 NDT.net. All rights reserved.
Copyright:
Copyright 2019 Elsevier B.V., All rights reserved.
PY - 2018
Y1 - 2018
N2 - Excessive deformations of beam-like structures and structural members (beams) may result in user distress, adversely affect neighbouring structural members, and even imperil structural safety. Therefore, determination of deformed shape of beams is of particular interest. Direct on-site long-term monitoring of the deformed shape is difficult, mostly due to limitations in available practical sensing technologies. As an alternative, indirect methods can be applied. As an example, strain can be monitored on-site and in long terms (e.g., using fibre optic sensors), converted into curvature by using appropriate equations, and curvature can be numerically double integrated to obtain the deformed shape. However, this method faces an important challenge, which is an accurate evaluation of error in the determined deformed shape. The error depends on several factors such as the accuracy measures of the monitoring system, geometrical and mechanical properties of the monitored beam, and in particular on the topology of the sensor network – number and spatial distribution of strain sensors. This research proposes a method for evaluation of error in deformed shape determined from strain measurements and double integration of curvature. As a result, it is possible to design sensor network, i.e., to determine minimum number of sensors needed to realize a wanted accuracy in deformed shape. Important finding is that error at a point depends on the value of curvature at that point, a constant related to curvature distribution along the beam, and the square of longitudinal distance between the sensors (i.e., density of the sensors). The method was validated in a laboratory and on a real structure – Streicker Bridge.
AB - Excessive deformations of beam-like structures and structural members (beams) may result in user distress, adversely affect neighbouring structural members, and even imperil structural safety. Therefore, determination of deformed shape of beams is of particular interest. Direct on-site long-term monitoring of the deformed shape is difficult, mostly due to limitations in available practical sensing technologies. As an alternative, indirect methods can be applied. As an example, strain can be monitored on-site and in long terms (e.g., using fibre optic sensors), converted into curvature by using appropriate equations, and curvature can be numerically double integrated to obtain the deformed shape. However, this method faces an important challenge, which is an accurate evaluation of error in the determined deformed shape. The error depends on several factors such as the accuracy measures of the monitoring system, geometrical and mechanical properties of the monitored beam, and in particular on the topology of the sensor network – number and spatial distribution of strain sensors. This research proposes a method for evaluation of error in deformed shape determined from strain measurements and double integration of curvature. As a result, it is possible to design sensor network, i.e., to determine minimum number of sensors needed to realize a wanted accuracy in deformed shape. Important finding is that error at a point depends on the value of curvature at that point, a constant related to curvature distribution along the beam, and the square of longitudinal distance between the sensors (i.e., density of the sensors). The method was validated in a laboratory and on a real structure – Streicker Bridge.
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M3 - Paper
AN - SCOPUS:85070880689
T2 - 9th European Workshop on Structural Health Monitoring, EWSHM 2018
Y2 - 10 July 2018 through 13 July 2018
ER -