Model-Based Position and Reflectivity Estimation of Fiber Bragg Grating Sensor Arrays

Werzinger S, Zibar D, Köppel M, Schmauß B (2018)


Publication Language: English

Publication Type: Journal article, Review article

Publication year: 2018

Journal

Publisher: MDPI AG

Book Volume: 18

Pages Range: 2268

Journal Issue: 7

DOI: 10.3390/s18072268

Abstract

We propose an efficient model-based signal processing approach for optical fiber sensing with fiber Bragg grating (FBG) arrays. A position estimation based on an estimation of distribution algorithm (EDA) and a reflectivity estimation method using a parametric transfer matrix model (TMM) are outlined in detail. The estimation algorithms are evaluated with Monte Carlo simulations and measurement data from an incoherent optical frequency domain reflectometer (iOFDR). The model-based approach outperforms conventional Fourier transform processing, especially near the spatial resolution limit, saving electrical bandwidth and measurement time. The models provide great flexibility and can be easily expanded in complexity to meet different topologies and to include prior knowledge of the sensors. Systematic errors due to crosstalk between gratings caused by multiple reflections and spectral shadowing could be further considered with the TMM to improve the performance of large-scale FBG array sensor systems. View Full-Text

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APA:

Werzinger, S., Zibar, D., Köppel, M., & Schmauß, B. (2018). Model-Based Position and Reflectivity Estimation of Fiber Bragg Grating Sensor Arrays. Sensors, 18(7), 2268. https://dx.doi.org/10.3390/s18072268

MLA:

Werzinger, Stefan, et al. "Model-Based Position and Reflectivity Estimation of Fiber Bragg Grating Sensor Arrays." Sensors 18.7 (2018): 2268.

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