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http://dx.doi.org/10.12652/Ksce.2020.40.6.0547

Multi-fidelity Data-fusion for Improving Strain accuracy using Optical Fiber Sensors  

Park, Young-Soo (Korea Institute of Civil Engineering and Building Technology)
Jin, Seung-Seop (Korea Institute of Civil Engineering and Building Technology)
Yoo, Chul-Hwan (Korea Institute of Civil Engineering and Building Technology)
Kim, Sungtae (Korea Institute of Civil Engineering and Building Technology)
Park, Young-Hwan (Korea Institute of Civil Engineering and Building Technology)
Publication Information
KSCE Journal of Civil and Environmental Engineering Research / v.40, no.6, 2020 , pp. 547-553 More about this Journal
Abstract
As aging infrastructures increase along with time, the efficient maintenance becomes more significant and accurate responses from the sensors are pre-requisite. Among various responses, strain is commonly used to detect damage such as crack and fatigue. Optical fiber sensor is one of the promising sensing techniques to measure strains with high-durability, immunity for electrical noise, long transmission distance. Fiber Bragg Grating (FBG) is a point sensor to measure the strain based on reflected signals from the grating, while Brillouin Optic Correlation Domain Analysis (BOCDA) is a distributed sensor to measure the strain along with the optical fiber based on scattering signals. Although the FBG provides the signal with high accuracy and reproducibility, the number of sensing points is limited. On the other hand, the BOCDA can measure a quasi-continuous strain along with the optical fiber. However, the measured signals from BOCDA have low accuracy and reproducibility. This paper proposed a multi-fidelity data-fusion method based on Gaussian Process Regression to improve the fidelity of the strain distribution by fusing the advantages of both systems. The proposed method was evaluated by laboratory test. The result shows that the proposed method is promising to improve the fidelity of the strain.
Keywords
Multi-fidelity modeling; Optical fiber sensor; Strain; Gaussian process regression; Complementary data-fusion;
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1 Amano, M., Okabe, Y., Takeda, N. and Ozaki, T. (2007). "Structural health monitoring of an advanced grid structure with embedded fiber bragg grating sensors." Structural Health Monitoring, Vol. 6, No. 4, pp. 309-324. DOI: 10.1177/1475921707081967.   DOI
2 Guemes, A., Fernandez-Lopez, A. and Soller, B. (2010). "Optical fiber distributed sensing - Physical principles and applications." Structural Health Monitoring, Vol. 9, No. 3, pp. 233-245. DOI: 10.1177/1475921710365263.   DOI
3 Hotate, K. (2000). "Measurement of brillouin gain spectrum distribution along an optical fiber using a correlation-based technique-proposal, experiment and simulation-." IEICE Transactions on Electronics, Vol. E83-C, No. 3, pp. 405-411.
4 Kennedy, M. C. and O'Hagan, A. (2001). "Bayesian calibration of computer models." Journal of the Royal Statistical Society, Series B (Statistical Methodology), Vol. 63, No. 3, pp. 425-464. DOI: 10.1111/1467-9868.00294.   DOI
5 Krohn, D. A., MacDougall, T. and Mendez, A. (2014). Fiber optic sensors: fundamentals and applications. Bellingham, WA: Spie Press.
6 Li, S. and Wu, Z. (2007). "Development of distributed long-gage fiber optic sensing system for structural health monitoring: structural health monitoring." An International Journal, Vol. 6, No. 2, pp. 133-143. DOI: 10.1177/1475921706072078.   DOI
7 Schulz, E., Speekenbrink, M. and Krause, A. (2018). "A tutorial on Gaussian process regression: Modelling, exploring, and exploiting functions." Journal of Mathematical Psychology, Vol. 85, pp. 1-16. DOI: 10.1016/j.jmp.2018.03.001.   DOI
8 Todd, M. D., Nichols, J. M., Trickey, S. T., Seaver, M., Nichols, C. J. and Virgin, L. N. (2007). "Bragg grating-based fibre optic sensors in structural health monitoring." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, Vol. 365, No. 1851, pp. 317-343. DOI: 10.1098/rsta.2006.1937.   DOI
9 Worden, K., Farrar, C. R., Manson, G. and Park, G. (2007). "The fundamental axioms of structural health monitoring." Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, Vol. 463, No. 2082, pp. 1639-1664. DOI: 10.1098/rspa.2007.1834.   DOI