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Optica Publishing Group
  • Journal of Lightwave Technology
  • Vol. 36,
  • Issue 4,
  • pp. 939-945
  • (2018)

Fiber Optic Measurement System for Fresnel Reflection Sensing: Calibration, Uncertainty, and Exemplary Application in Temperature-Modulated Isothermal Polymer Curing

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Abstract

Fiber Bragg grating (FBG) sensors and Fresnel reflectometer sensors have emerged as promising tools for monitoring process state parameters during composite manufacturing. However, multifunctional fiber optic sensor systems exploiting the versatile nature of these sensors are not commercially available. In principle, most FBG measurement systems are equipped with the required hardware to measure the refractive index (RI) by interrogating Fresnel reflectometer sensors. However, the implications of using an FBG system for this purpose have not been previously studied. Therefore, we calibrated a commercial FBG measurement system in the refractive index range between 1.3 and 1.6 at 1550 nm, based on data comparison with an independent RI measurement technique, and determined the measurement uncertainty. Additionally, we investigate the suitability of the proposed Fresnel reflectometer sensor for use in temperature-modulated isothermal epoxy curing experiments for detecting the glass transition by exploiting a concept that resembles temperature modulated optical refractometry. This paper describes in detail the calibration routine, the determination of the measurement uncertainty, and the application of Fresnel reflectometer sensors for glass transition detection during isothermal curing. We observed an offset between the measured RI and the theoretical value in the range of $10^{{{\hbox{--}} 3}}$ . The measurement system uncertainty was found to be of the order of $10^{{{\hbox{--}} 4}}$ . That is comparable to the accuracy of most commercial refractometers. Furthermore, we showed that Fresnel reflectometer sensors are suitable for glass transition detection during isothermal curing. The results show that commercial FBG measurement systems are viable options for multifunctionality sensing in online process monitoring applications.

© 2017 IEEE

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