SOLVING THE INVERSE SCATTERING PROBLEM WITH DIFFERENTIAL EVOLUTION: AN EXPERIMENTAL VALIDATION
Keywords:Computational Intelligence, Differential Evolution, Fiber Bragg Gratings, Optical Sensors, Strain Sensing
This work shows the experimental validation of a method developed for determining the strain profile applied to a fiber Bragg grating by solving the inverse scattering problem. The non-uniform strain profile is recovered by formulating an optimization problem, solved with an algorithm based on differential evolution. The method has proved to be able of recovering the shape and approximate amplitude of the actual strain profile applied to the FBG, opening new perspectives for optical sensing with fiber Bragg gratings.
sensors,” Journal of Lightwave Technology, vol. 15, no. 8, pp. 1442-1463, 1997.
 L. Negri, A. Nied, H. Kalinowski, and A. Paterno, “Benchmark for Peak Detection Algorithms in Fiber Bragg Grating
Interrogation and a New Neural Network for its Performance Improvement,” Sensors, vol. 11, no. 12, pp. 3466-3482,
 D. Tosi, M. Olivero, and G. Perrone, “Performance analysis of peak tracking techniques for fiber Bragg grating
interrogation systems,” Journal of Microwaves, Optoelectronics and Electromagnetic Applications, vol. 11, pp. 252-
 Y.-J. Rao, “In-fibre Bragg grating sensors,” Meas. Sci. Technol., vol. 8, n. 4, pp. 355-375, 1997.
 N. Hirayama, Y. Sano, “Fiber Bragg grating temperature sensor for practical use,” ISA Trans., vol. 39, no. 2, pp. 169-
 J.-S. Heo, J.-H. Chung, and J.-J. Lee, “Tactile sensor arrays using fiber Bragg grating sensors,” Sensors Actuators A
Phys., vol. 126, no. 2, pp. 312-327, 2006.
 S. Huang, M. Leblanc, M. M. Ohn, and R. M. Measures, “Bragg intragrating structural sensing,” Applied Optics, vol.
34, no. 22, pp. 5003-5009, 1995.
 J. Skaar and R. Feced, “Reconstruction of gratings from noisy reflection data,” Journal of the Optical Society of
America. A: Optics and Image Science, and Vision, vol. 19, no. 11, pp. 2229-2237, 2002.
 M. Leblanc, S. Y. Huang, M. Ohn, R. M. Measures, A. Guemes, and A. Othonos, “Distributed strain measurement
based on a fiber Bragg grating and its reflection spectrum analysis,” Optics Letters, vol. 21, no. 17, pp. 1405-1407,
 M. Ohn, S. Huang, R. Measures, and J. Chwang, “Arbitrary strain profile measurement within fibre gratings using
interferometric Fourier transform technique,” Electronics Letters, vol. 33, no. 14, pp. 1242-1243, 1997.
 M. A. Muriel, J. Azaña, and A. Carballar, “Fiber grating synthesis by use of time-frequency representations,” Optics
Letters, vol. 23, no. 19, pp. 1526-1528, 1998.
 H.-C. Cheng and Y.-L. Lo, “Arbitrary strain distribution measurement using a genetic algorithm approach and two fiber
Bragg grating intensity spectra,” Optics Communications, vol. 239, no. 4-6, pp. 323-332, 2004.
 C. C. Cheng, Y. L. Lo, W. Y. Li, C. T. Kuo, and H. C. Cheng, “Estimations of fiber Bragg grating parameters and strain
gauge factor using optical spectrum and strain distribution information,” Appl. Opt., vol. 46, no. 21, pp. 4555-4562,
 L. H. Negri, H. S. Lopes, M. Muller, J. L. Fabris, and A. S. Paterno, “An efficient method to determine strain profiles
on FBGs by using differential evolution and GPU,” in 2015 Latin America Congress on Computational Intelligence
(LA-CCI), pp. 1-6, 2015.
 J. Zhang and A. C. Sanderson, “JADE: Adaptive Differential Evolution with Optional External Archive,” IEEE Trans.
Evol. Comput., vol. 13, no. 5, pp. 945-958, 2009.
 M. J. D. Sousa, J. C. W. A. Costa, R. M. D. Souza, and R. V. M. P. Pantoja, “FBG optimization using spline encoded
evolution strategy,” Journal of Microwaves, Optoelectronics and Electromagnetic Applications, vol. 10, pp. 165 - 178,
 K. O. Hill, B. Malo, F. Bilodeau, D. C. Johnson, and J. Albert, “Bragg gratings fabricated in monomode photosensitive
optical fiber by UV exposure through a phase mask,” Appl. Phys. Lett., vol. 62, no. 10, pp. 1035-1037, 1993.