Abstract

This work targets a remarkable quasi-distributed temperature sensor based on an apodized fiber Bragg grating. To achieve this, the mathematical formula for a proposed apodization function is carried out and tested. Then, an optimization parametric process required to achieve the remarkable accuracy that is based on coupled mode theory (CMT) is done. A detailed investigation for the side lobe analysis, which is a primary judgment factor, especially in quasi-distributed configuration, is investigated. A comparison between elite selection of apodization profiles (extracted from related literatures) and the proposed modified-Nuttal profile is carried out covering reflectivity peak, full width half maximum (FWHM), and side lobe analysis. The optimization process concludes that the proposed modified-Nuttal profile with a length (L) of 15 mm and refractive index modulation amplitude (Δn) of 1.4×104 is the optimum choice for single-stage and quasi-distributed temperature sensor networks. At previous values, the proposed profile achieves an acceptable reflectivity peak of 100.426dB, acceptable FWHM of 0.0808 nm, lowest side lobe maximum (SL max) of 7.037×1012dB, lowest side lobe average (SL avg) of 3.883×1012dB, and lowest side lobe suppression ratio (SLSR) of 1.875×1011dB. These optimized characteristics lead to an accurate single-stage sensor with a temperature sensitivity of 0.0136 nm/°C. For the quasi-distributed scenario, a noteworthy total isolation of 91 dB is achieved without temperature, and an isolation of 4.83 dB is achieved while applying temperature of 110°C for a five-stage temperature-sensing network. Further investigation is made proving that consistency in choosing the apodization profile in the quasi-distributed network is mandatory. If the consistency condition is violated, the proposed profile still survives with a casualty of side lobe level rise of 73.2070dB when adding uniform apodization and 46.4823dB when adding Gaussian apodization to the five-stage modified-Nuttall temperature-sensing network.

© 2018 Optical Society of America

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