Novel approach peak tracking method for FBG: Gaussian polynomial technique

Authors

  • Bunga Meyzia Department of Physics, Universitas Riau, Pekanbaru 28293, Indonesia
  • Saktioto Saktioto Department of Physics, Universitas Riau, Pekanbaru 28293, Indonesia
  • Tengku Emrinaldi Department of Physics, Universitas Riau, Pekanbaru 28293, Indonesia
  • Nadiah Wanara Department of Physics, Universitas Riau, Pekanbaru 28293, Indonesia
  • Dwi Hanto Research Center for Photonics, BRIN - KST BJ HABIBIE, South Tangerang 15314, Indonesia
  • Bambang Widyatmoko Research Center for Photonics, BRIN - KST BJ HABIBIE, South Tangerang 15314, Indonesia
  • Agitta Rianaris Research Center for Photonics, BRIN - KST BJ HABIBIE, South Tangerang 15314, Indonesia
  • Mohamad Syahadi Research Center for Photonics, BRIN - KST BJ HABIBIE, South Tangerang 15314, Indonesia
  • Haryana Mohd Hairi Department of Physics, Universiti Teknologi MARA, Shah Alam 40450, Malaysia
  • Mohammed Fadhali Department of Physics, Jazan University, Jazan 45142, Saudi Arabia \\ Department of Physics, Ibb University, Ibb 70270, Yemen

DOI:

https://doi.org/10.59190/stc.v4i3.262

Keywords:

Algorithm, FBG Uniform, Fiber Bragg Grating, Gaussian Polynomial, Interrogator

Abstract

This paper presents a novel approach for tracking the peaks in the FBG spectrum using the Gaussian polynomial method. The proposed algorithm involves preprocessing the FBG signal, detecting the peaks, and fitting the peaks with a Gaussian function. The performance of the algorithm is evaluated using both simulated and experimental FBG spectra. This method involves fitting a Gaussian function to the peak of interest and using the fitted parameters to estimate peak height, width, and location. The method is highly accurate and precise and can provide detailed information about peak shape and position, making it effective for tracking complex or overlapping peaks. However, the method can be computationally intensive and may require careful selection of initial parameters to ensure accurate results. Despite these limitations, the Gaussian polynomial method is a powerful tool for peak tracking and analysis in various application.

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Published

2024-06-30

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