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Full-Scale Prestress Loss Monitoring of Damaged RC Structures Using Distributed Optical Fiber Sensing Technology

For the safety of prestressed structures, prestress loss is a critical issue that will increase with structural damage, so it is necessary to investigate prestress loss of prestressed structures under different damage scenarios. Unfortunately, to date, no qualified techniques are available due to di...

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Detalles Bibliográficos
Autores principales: Lan, Chunguang, Zhou, Zhi, Ou, Jinping
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Molecular Diversity Preservation International (MDPI) 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3386689/
https://www.ncbi.nlm.nih.gov/pubmed/22778590
http://dx.doi.org/10.3390/s120505380
Descripción
Sumario:For the safety of prestressed structures, prestress loss is a critical issue that will increase with structural damage, so it is necessary to investigate prestress loss of prestressed structures under different damage scenarios. Unfortunately, to date, no qualified techniques are available due to difficulty for sensors to survive in harsh construction environments of long service life and large span. In this paper, a novel smart steel strand based on the Brillouin optical time domain analysis (BOTDA) sensing technique was designed and manufactured, and then series of tests were used to characterize properties of the smart steel strands. Based on prestress loss principle analysis of damaged structures, laboratory tests of two similar beams with different damages were used to verify the concept of full-scale prestress loss monitoring of damaged reinforced concrete (RC) beams by using the smart steel strands. The prestress losses obtained from the Brillouin sensors are compared with that from conventional sensors, which provided the evolution law of prestress losses of damaged RC beams. The monitoring results from the proposed smart strand can reveal both spatial distribution and time history of prestress losses of damaged RC beams.