Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Structural Deformation Sensing Based on Distributed Optical Fiber Monitoring Technology and Neural Network
Structural deformation monitoring is vital to the safety of concrete structures. However, the distributed deformation of structures cannot be easily obtained using existing monitoring methods in civil engineering. To this end, this paper proposes a method to estimate the continuous deformation of concrete beams by utilizing the distributed optical fiber monitoring technology. In this method, optical fibers and a total station are used to obtain the strain and deformation distribution curves of a concrete beam, respectively. Subsequently, these curves are inputted to a back propagation network as training samples to learn their relationships. The results show that the deformation value of trained neural network is very close to that of the total station, with a maximum error of only 2.7% (0.3 mm). The linear regression analysis shows a goodness of fit R2 greater than 0.98, which confirms the reliability of the simulations results.
Structural Deformation Sensing Based on Distributed Optical Fiber Monitoring Technology and Neural Network
Structural deformation monitoring is vital to the safety of concrete structures. However, the distributed deformation of structures cannot be easily obtained using existing monitoring methods in civil engineering. To this end, this paper proposes a method to estimate the continuous deformation of concrete beams by utilizing the distributed optical fiber monitoring technology. In this method, optical fibers and a total station are used to obtain the strain and deformation distribution curves of a concrete beam, respectively. Subsequently, these curves are inputted to a back propagation network as training samples to learn their relationships. The results show that the deformation value of trained neural network is very close to that of the total station, with a maximum error of only 2.7% (0.3 mm). The linear regression analysis shows a goodness of fit R2 greater than 0.98, which confirms the reliability of the simulations results.
Structural Deformation Sensing Based on Distributed Optical Fiber Monitoring Technology and Neural Network
KSCE J Civ Eng
Hou, Gong-Yu (Autor:in) / Li, Zi-Xiang (Autor:in) / Wang, Kai-Di (Autor:in) / Hu, Jin-Xin (Autor:in)
KSCE Journal of Civil Engineering ; 25 ; 4304-4313
01.11.2021
10 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
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