Abstract
This paper introduces a concept of smart structural elements for the real-time condition monitoring of bridges. These are prefabricated reinforced concrete elements embedding a permanent sensing system and capable of self-diagnosis when in operation. The real-time assessment is automatically controlled by a numerical algorithm founded on Bayesian logic: the method assigns a probability to each possible damage scenario, and estimates the statistical distribution of the damage parameters involved (such as location and extent). To verify the effectiveness of the technology, we produced and tested in the laboratory a reduced-scale smart beam prototype. The specimen is 3.8 m long and has cross-section 0.3 by 0.5m, and has been prestressed using a Dywidag bar, in such a way as to control the preload level. The sensor system includes a multiplexed version of SOFO interferometric sensors mounted on a composite bar, along with a number of traditional metal-foil strain gauges. The method allowed clear recognition of increasing fault states, simulated on the beam by gradually reducing the prestress level.
Original language | English |
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Title of host publication | Proceedings of SPIE - The International Society for Optical Engineering |
Volume | 6932 |
DOIs | |
Publication status | Published - 8 Apr 2008 |
Event | Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2008 - San Diego, CA, United States Duration: 10 Mar 2008 → 13 Mar 2008 |
Conference
Conference | Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2008 |
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Country/Territory | United States |
City | San Diego, CA |
Period | 10/03/08 → 13/03/08 |
Keywords
- Bayesian analysis
- fiber optic sensors
- laboratory experiment
- smart beam
- SOFO
- medical diagnostics