Benchmark for standard and computationally intelligent peak detection algorithms for fiber Bragg grating sensors

• Main Author: Negri L.H.*
• Publication Date: 2011
• Other Authors: Kalinowski H.J., Paterno, Aleksander Sade
• Format: Conference object
• Language: eng
• Source: Repositório Institucional da Udesc
• dARK ID: ark:/33523/001300000tq14
• Download full: https://repositorio.udesc.br/handle/UDESC/9517

Implementation and comparison of peak detection algorithms for fiber Bragg gratings spectra have been implemented and made publicly available. Benchmark experiments were performed by measuring accuracy, precision and efficiency of currently used algorithms, namely the centroid, least squares gaussian and polynomial fitting, and computational intelligence techniques using particle swarm optimization and perceptron neural network. Considering noisy apodized and uniform FBG spectra in the detection, it is shown that there is no general optimal algorithm for fast peak determination with high accuracy and precision, but it would be easier to choose quasi-optimal algorithms with the more general guidelines presented. © 2011 Copyright Society of Photo-Optical Instrumentation Engineers (SPIE).