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

Lucas H. Negri; Hypolito J. Kalinowski; Aleksander S. Paterno

doi:10.1117/12.885964

17 May 2011 Benchmark for standard and computationally intelligent peak detection algorithms for fiber Bragg grating sensors

Lucas H. Negri, Hypolito J. Kalinowski, Aleksander S. Paterno

Author Affiliations +

Proceedings Volume 7753, 21st International Conference on Optical Fiber Sensors; 77537F (2011) https://doi.org/10.1117/12.885964
Event: 21st International Conference on Optical Fibre Sensors (OFS21), 2011, Ottawa, Canada

Abstract

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.

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Lucas H. Negri, Hypolito J. Kalinowski, and Aleksander S. Paterno "Benchmark for standard and computationally intelligent peak detection algorithms for fiber Bragg grating sensors", Proc. SPIE 7753, 21st International Conference on Optical Fiber Sensors, 77537F (17 May 2011); https://doi.org/10.1117/12.885964

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