TY - JOUR
T1 - Detecting, localizing, and quantifying damage using two-dimensional sensing sheet
T2 - lab test and field application
AU - Kumar, Vivek
AU - Acot, Bianca
AU - Aygun, Levent E.
AU - Wagner, Sigurd
AU - Verma, Naveen
AU - Sturm, James
AU - Glisic, Branko
N1 - Funding Information:
This research was, in part, supported by the USDOT OST-R UTC Program, grant no. 69A3551847102, enabled through the Center for Advanced Infrastructure and Transportation (CAIT) at the Rutgers University (subcontract agreement no. 0615).
Publisher Copyright:
© 2021, Springer-Verlag GmbH Germany, part of Springer Nature.
PY - 2021/9
Y1 - 2021/9
N2 - Damage to structures in the form of cracks could reduce safety and induce high maintenance cost. Structural health monitoring (SHM) is increasingly employed to detect damage in the structure and inform the stakeholders in a timely manner to allow rehabilitation actions. Reliable crack detection, localization, and quantification are, hence, extremely important. To achieve this goal, a dense network of sensors is often required. Damages even a meter away from sensors are often unable to be detected reliably by a sensing system. Creating a dense network of sensors using the commonly used point sensors (e.g., strain gages) or distributed one-dimensional sensors (e.g., fiber-optic sensors) is expensive and often practically impossible. Sensing sheet is a distributed two-dimensional thin-film sensor comprising of a dense array of resistive strain gage units developed at Princeton University. Based on the principles of large-area electronics (LAE), this thin-film sensor provides an affordable solution to reliably detect and localize damage. This paper derives analytical models for damage detection, localization, and quantification based on sensing sheet. Laboratory experiments are performed by creating artificial damage to verify these models and highlight their uses. Further, the damage quantification algorithm is used to estimate the crack opening in a shrinkage crack on the foundation of the pedestrian bridge at Princeton University. Finally, the results and future research directions are discussed.
AB - Damage to structures in the form of cracks could reduce safety and induce high maintenance cost. Structural health monitoring (SHM) is increasingly employed to detect damage in the structure and inform the stakeholders in a timely manner to allow rehabilitation actions. Reliable crack detection, localization, and quantification are, hence, extremely important. To achieve this goal, a dense network of sensors is often required. Damages even a meter away from sensors are often unable to be detected reliably by a sensing system. Creating a dense network of sensors using the commonly used point sensors (e.g., strain gages) or distributed one-dimensional sensors (e.g., fiber-optic sensors) is expensive and often practically impossible. Sensing sheet is a distributed two-dimensional thin-film sensor comprising of a dense array of resistive strain gage units developed at Princeton University. Based on the principles of large-area electronics (LAE), this thin-film sensor provides an affordable solution to reliably detect and localize damage. This paper derives analytical models for damage detection, localization, and quantification based on sensing sheet. Laboratory experiments are performed by creating artificial damage to verify these models and highlight their uses. Further, the damage quantification algorithm is used to estimate the crack opening in a shrinkage crack on the foundation of the pedestrian bridge at Princeton University. Finally, the results and future research directions are discussed.
KW - Analytical modeling
KW - Concrete bridge application
KW - Crack detection, localization and quantification
KW - Quasi-distributed direct sensing
KW - Structural health monitoring
KW - Two-dimensional sensing
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U2 - 10.1007/s13349-021-00498-5
DO - 10.1007/s13349-021-00498-5
M3 - Article
AN - SCOPUS:85107782636
SN - 2190-5452
VL - 11
SP - 1055
EP - 1075
JO - Journal of Civil Structural Health Monitoring
JF - Journal of Civil Structural Health Monitoring
IS - 4
ER -