International Journal of Circuits, Systems and Signal Processing

   
E-ISSN: 1998-4464
Volume 15, 2021

Notice: As of 2014 and for the forthcoming years, the publication frequency/periodicity of NAUN Journals is adapted to the 'continuously updated' model. What this means is that instead of being separated into issues, new papers will be added on a continuous basis, allowing a more regular flow and shorter publication times. The papers will appear in reverse order, therefore the most recent one will be on top.

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Volume 15, 2021

Title of the Paper: An Improved Temperature Compensation Method for Fiber Bragg Grating Pressure Sensor Based on Extreme Learning Machine

Authors: Hongying Guo, Jiang Chen, Zhumei Tian, Aizhen Wang

Pages: 1091-1098 

DOI: 10.46300/9106.2021.15.118     XML

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Abstract: According to the problem of the sensor nonlinear changes occur at high temperatures, extreme learning machine model, is presented in this thesis the pressure sensitive grating and removing the temperature of the grating experiment data for training, establish a nonlinear model of wavelength, temperature, predict the experimental temperature, then the temperature data of pressure-sensitive grating the training set of training samples, the nonlinear model, temperature - wavelength prediction test set sample output wavelength, achieve the goal of improved temperature compensation method. The experimental results show that the algorithm can achieve a more ideal temperature compensation effect.