This paper presents a benchmark for peak detection algorithms employed in fiber Bragg grating spectrometric interrogation systems. The accuracy, precision, and computational performance of currently used algorithms and those of a new proposed artificial neural network algorithm are compared. Centroid and gaussian fitting algorithms are shown to have the highest precision but produce systematic errors that depend on the FBG refractive index modulation profile. The proposed neural network displays relatively good precision with reduced systematic errors and improved computational performance when compared to other networks. Additionally, suitable algorithms may be chosen with the general guidelines presented.
This work reports a modified flame-brush technique to fabricate fiber tapers with arbitrary waist profiles. The flame-brush approach is used to produce small step reductions in the fiber diameter, or step-tapers, with a constant speed flame brush sweep, while the fiber is uniformly stretched. Arbitrary waist profiles in tapers are fabricated by approximating the taper diameter function to any monotonic function of the fiber length while combining a superposition of step-tapers. This method to produce the arbitrary profiles is described and a set of tapers with dissimilar transition regions are fabricated for its validation.
The implementation of a radial-basis function network to approximate spectra of the signal reflected by a fibre Bragg grating sensor is reported. This algorithm helps the interpretation of the data acquired with equipment as an optical spectrum analyser. Results using a double-peaked spectrum from a uniform fibre Bragg grating sensor show that the common practice of fitting the spectrum with different interpolation methods and finding its peak, or directly finding the maximum intensity position of the raw spectrum, would cause a larger error when compared to searching for the peak of an approximated spectrum using the proposed neural network. An example is demonstrated through two experiments measuring the volumetric shrinkage of polymeric resin using a uniform FBG and a HiBi FBG embedded in the material. The obtained accuracy is higher than that obtained with the simple non-processed peak detection.
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