Brillouin optical frequency domain analysis in polymer optical fiber

2014 ◽  
Author(s):  
Aldo Minardo ◽  
Romeo Bernini ◽  
Luigi Zeni
2019 ◽  
Vol 10 (3) ◽  
pp. 243-252
Author(s):  
T. P. Yanukovich ◽  
A. V. Polyakov

Due to the development of automation and control systems, methods and devices for measuring of electric current large values are of great interest. The aim of the work was to develop a schematic diagram of a distributed current strength sensor based on the Brillouin optical frequency domain analysis; to create a mathematical model of the sensor to demonstrate its work and to calculate the basic parameters of the sensor. To provide the measurement optical fiber with conductive coating is used. Between the current bus, where current is measured, and conductive coating the Ampere force arises. Strain occurs in optical fiber due to this force. Stimulated Brillouin scattering has the strain dependent characteristic frequency. Shift of the characteristic frequency allows to measure current in the bus. To measure the characteristic frequency and the location of its shift Brillouin optical frequency domain analysis is used.The mathematical model of sensor operation based on tree-wave model of stimulated Brillouin scattering is demonstrated. This model allows calculating intensity of optical signal in the fiber in dependence of characteristic frequency shift. Brillouin optical frequency domain analysis uses inverse Fourier transform to obtain pulse response.A schematic diagram of a distributed current sensor based on the method of Brillouin optical frequency domain analysis is presented. An a priori estimate of parameters of the measuring system was carried out on the basis of the mathematical model of stimulated Brillouing scattering in an optical fiber. The spatial resolution of the sensor when determining the length and location of fiber sections was 0.06 m. The resolution of the sensor was 0.22 kA, the maximum value of the current strength was 25 kA. Dependence of the sensor operation at different powers of the laser used was investigated. The refractive index change influence on the result of measurements was estimated.


Sensors ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 2724
Author(s):  
Christos Karapanagiotis ◽  
Aleksander Wosniok ◽  
Konstantin Hicke ◽  
Katerina Krebber

To our knowledge, this is the first report on a machine-learning-assisted Brillouin optical frequency domain analysis (BOFDA) for time-efficient temperature measurements. We propose a convolutional neural network (CNN)-based signal post-processing method that, compared to the conventional Lorentzian curve fitting approach, facilitates temperature extraction. Due to its robustness against noise, it can enhance the performance of the system. The CNN-assisted BOFDA is expected to shorten the measurement time by more than nine times and open the way for applications, where faster monitoring is essential.


1996 ◽  
Vol 21 (17) ◽  
pp. 1402 ◽  
Author(s):  
Dieter Garus ◽  
Torsten Gogolla ◽  
Katerina Krebber ◽  
Frank Schliep

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