TY - JOUR
T1 - Identifying time periods of minimal thermal gradient for temperature-driven structural health monitoring
AU - Reilly, John
AU - Glisic, Branko
N1 - Funding Information:
Acknowledgments: This research has been supported by National Science Foundation Grant CMMI-1434455. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation. Matthew Yarnold at Texas A&M University and Brittany Murphy at Tennessee Technological University contributed to the underlying concepts for the formulation of TD-SHM. The Streicker Bridge project has taken a great effort from 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, USA; Geoffrey Gettelfinger; James P Wallace; Miles Hersey; Paul Prucnal; Yanhua Deng; Mable Fok; 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. Dorotea Sigurdardottir and Hiba Abdel-Jaber provided invaluable work in data processing and cleansing for the Streicker Bridge, among various other contributions. Joseph Vocaturo provided technical assistance to the installation of the displacement sensors.
Publisher Copyright:
© 2018 by the authors. Licensee MDPI, Basel, Switzerland.
PY - 2018/3/1
Y1 - 2018/3/1
N2 - Temperature changes play a large role in the day to day structural behavior of structures, but a smaller direct role in most contemporary Structural Health Monitoring (SHM) analyses. Temperature-Driven SHM will consider temperature as the principal driving force in SHM, relating a measurable input temperature to measurable output generalized strain (strain, curvature, etc.) and generalized displacement (deflection, rotation, etc.) to create three-dimensional signatures descriptive of the structural behavior. Identifying time periods of minimal thermal gradient provides the foundation for the formulation of the temperature–deformation–displacement model. Thermal gradients in a structure can cause curvature in multiple directions, as well as non-linear strain and stress distributions within the cross-sections, which significantly complicates data analysis and interpretation, distorts the signatures, and may lead to unreliable conclusions regarding structural behavior and condition. These adverse effects can be minimized if the signatures are evaluated at times when thermal gradients in the structure are minimal. This paper proposes two classes of methods based on the following two metrics: (i) the range of raw temperatures on the structure, and (ii) the distribution of the local thermal gradients, for identifying time periods of minimal thermal gradient on a structure with the ability to vary the tolerance of acceptable thermal gradients. The methods are tested and validated with data collected from the Streicker Bridge on campus at Princeton University.
AB - Temperature changes play a large role in the day to day structural behavior of structures, but a smaller direct role in most contemporary Structural Health Monitoring (SHM) analyses. Temperature-Driven SHM will consider temperature as the principal driving force in SHM, relating a measurable input temperature to measurable output generalized strain (strain, curvature, etc.) and generalized displacement (deflection, rotation, etc.) to create three-dimensional signatures descriptive of the structural behavior. Identifying time periods of minimal thermal gradient provides the foundation for the formulation of the temperature–deformation–displacement model. Thermal gradients in a structure can cause curvature in multiple directions, as well as non-linear strain and stress distributions within the cross-sections, which significantly complicates data analysis and interpretation, distorts the signatures, and may lead to unreliable conclusions regarding structural behavior and condition. These adverse effects can be minimized if the signatures are evaluated at times when thermal gradients in the structure are minimal. This paper proposes two classes of methods based on the following two metrics: (i) the range of raw temperatures on the structure, and (ii) the distribution of the local thermal gradients, for identifying time periods of minimal thermal gradient on a structure with the ability to vary the tolerance of acceptable thermal gradients. The methods are tested and validated with data collected from the Streicker Bridge on campus at Princeton University.
KW - Fiber optic sensors
KW - Prestressed concrete bridge
KW - Temperature-driven structural health monitoring (TD-SHM)
KW - Thermal gradients
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U2 - 10.3390/s18030734
DO - 10.3390/s18030734
M3 - Article
C2 - 29494496
AN - SCOPUS:85042778442
SN - 1424-3210
VL - 18
JO - Sensors
JF - Sensors
IS - 3
M1 - 734
ER -