Transverse Load Discrimination in Long-Period Fiber Grating via Artificial Neural Network

Authors

  • F. O. Barino
  • F. S. Delgado
  • A. B. dos Santos

DOI:

https://doi.org/10.1590/2179-10742020v19i11809

Keywords:

artfificial neural network, long period grating, optical fiber sensor, transverse load

Abstract

We present a general investigation of a Long-Period Grating (LPG) for transverse strain measurement. The transverse strain sensing characteristics, for instance, the load intensity and azimuthal angle, are analyzed with the data set generated by the long-period grating sensor, which can be detected by using artificial nerural network (ANN). Furthermore, we evaluate and compare the predictive performance of the interrogation model considering the square correlation coefficient (R2) and root mean square error (RMSE). The results indicate that the ANN model could be successfully employed to estimate the load intensity and azimuthal angle.

References

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Yiping Wang, Dong Ning Wang, Wei Jin, and Yun

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Published

2020-03-19

How to Cite

Barino, F. O., Delgado, F. S., & dos Santos, A. B. (2020). Transverse Load Discrimination in Long-Period Fiber Grating via Artificial Neural Network. Journal of Microwaves, Optoelectronics and Electromagnetic Applications (JMOe), 19(1), 1-10. https://doi.org/10.1590/2179-10742020v19i11809

Issue

Section

Regular Papers