Benchmark for Peak Detection Algorithms in Fiber Bragg Grating Interrogation and a New Neural Network for its Performance ImprovementReport as inadecuate




Benchmark for Peak Detection Algorithms in Fiber Bragg Grating Interrogation and a New Neural Network for its Performance Improvement - Download this document for free, or read online. Document in PDF available to download.

1

Department of Electrical Engineering, Santa Catarina State University UDESC, Joinville 89223-100, Brazil

2

Graduate School of Electrical Engineering and Computer Science, Federal University of Technology-ParanĂ¡ UTFPR, Curitiba 80230-901, Brazil





*

Author to whom correspondence should be addressed.



Abstract 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. View Full-Text

Keywords: fiber Bragg grating; optical sensing; peak detection; fitting; optimization fiber Bragg grating; optical sensing; peak detection; fitting; optimization





Author: Lucas Negri 1, Ademir Nied 1, Hypolito Kalinowski 2 and Aleksander Paterno 1,*

Source: http://mdpi.com/



DOWNLOAD PDF




Related documents