Optical Fiber System Transmission Considerations

1977 ◽  
Author(s):  
T. A. Eppes ◽  
J. E. Goell
Keyword(s):  
Optical Fiber ◽  
Fiber System

scholarly journals Morphology-dependent resonances of a microsphere–optical fiber system

1996 ◽  
Vol 21 (10) ◽  
pp. 695 ◽  
Author(s):  
Giora Griffel ◽  
John Connolly ◽  
Nancy Morris ◽  
Stephen Arnold ◽  
Dogan Taskent ◽  
...  
Keyword(s):  
Optical Fiber ◽  
Fiber System ◽  
Morphology Dependent Resonances

scholarly journals A Fiber Bragg Grating Based Torsional Vibration Sensor for Rotating Machinery

Sensors ◽  
2018 ◽  
Vol 18 (8) ◽  
pp. 2669 ◽  
Author(s):  
Jingjing Wang ◽  
Li Wei ◽  
Ruiya Li ◽  
Qin Liu ◽  
Lingling Yu
Keyword(s):  
Optical Fiber ◽  
Fiber Bragg Grating ◽  
Torsional Vibration ◽  
Electromagnetic Interference ◽  
Vibration Sensor ◽  
Vibration Measurement ◽  
Bragg Grating ◽  
Structural Parameter ◽  
Measurement Sensitivity ◽  
Fiber System

This paper proposes a new type of torsional vibration sensor based on fiber Bragg grating (FBG). The sensor has two mass ball optical fiber systems. The optical fiber is directly treated as an elastomer and a mass ball is fixed in the middle of the fiber in each mass ball fiber system, which is advantageously small, lightweight, and has anti-electromagnetic interference properties. The torsional vibration signal can be calculated by the four FBGs’ wavelength shifts, which are caused by mass balls. The difference in the two sets of mass ball optical fiber systems achieves anti-horizontal vibration and anti-temperature interference. The principle and model of the sensor, as well as numerical analysis and structural parameter design, are introduced. The experimental conclusions show that the minimum torsional natural frequency of the sensor is 27.35 Hz and the torsional vibration measurement sensitivity is 0.3603 pm/(rad/s2).

REPRESENTATION FOR DISPERSION FORMULA OF OPTICAL FIBER USING HYBRID TECHNIQUE

2008 ◽  
Vol 19 (02) ◽  
pp. 205-213 ◽  
Author(s):  
AMR RADI
Keyword(s):  
Neural Network ◽  
Refractive Index ◽  
Optical Fiber ◽  
Hybrid Technique ◽  
Training Set ◽  
Fiber System ◽  
Output Data ◽  
Input And Output ◽  
Dispersion Formula ◽  
The Neural Network

Genetic Algorithm (GA) has been used to find the optimal neural network (NN) solution (i.e., hybrid technique) which represents dispersion formula of optical fiber. An efficient NN has been designed by GA to simulate the dynamics of the optical fiber system which is nonlinear. Without any knowledge about the system, we have used the input and output data to build a prediction model by NN. The neural network has been trained to produce a function that describes nonlinear system which studies the dependence of the refractive index of the fiber core on the wavelength and temperature. The trained NN model shows a good performance in matching the trained distributions. The NN is then used to predict refractive index that is not presented in the training set. The predicted refractive index had been matched to the experimental data effectively.

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