Abstract
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.
Original language | English (US) |
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Pages (from-to) | 1055-1075 |
Number of pages | 21 |
Journal | Journal of Civil Structural Health Monitoring |
Volume | 11 |
Issue number | 4 |
DOIs | |
State | Published - Sep 2021 |
All Science Journal Classification (ASJC) codes
- Civil and Structural Engineering
- Safety, Risk, Reliability and Quality
Keywords
- Analytical modeling
- Concrete bridge application
- Crack detection, localization and quantification
- Quasi-distributed direct sensing
- Structural health monitoring
- Two-dimensional sensing