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Experimental Dataset for Fiber Optic Specklegram Sensing Under Thermal Conditions and Use in a Deep Learning Interrogation Scheme

Author

Listed:
  • Francisco J. Vélez

    (Facultad de Ingeniería, Universidad Cooperativa de Colombia, Medellín 050012, Colombia
    School of Applied Sciences and Engineering, EAFIT University, Medellín 050022, Colombia)

  • Juan D. Arango

    (Facultad de Ciencias Exactas y Aplicadas, Instituto Tecnológico Metropolitano, Medellín 050013, Colombia)

  • Víctor H. Aristizábal

    (Facultad de Ingeniería, Universidad Cooperativa de Colombia, Medellín 050012, Colombia)

  • Carlos Trujillo

    (School of Applied Sciences and Engineering, EAFIT University, Medellín 050022, Colombia)

  • Jorge A. Herrera-Ramírez

    (Facultad de Ciencias Exactas y Aplicadas, Instituto Tecnológico Metropolitano, Medellín 050013, Colombia)

Abstract

This dataset comprises specklegram images acquired from a multimode optical fiber subjected to varying thermal conditions. Designed for training neural networks focused on developing Fiber Optic Specklegram Sensors (FSSs), these experimental data enable the detection of changes in speckle patterns corresponding to applied temperature variations. The dataset includes 24,528 images captured over a temperature range from 25 °C to 200 °C, with incremental steps of approximately 0.175 °C. Key acquisition parameters include a wavelength of 633 nm, a sensing zone length of 20 mm, and a multimode fiber with a core diameter of 62.5 μm. This dataset supports developing and validating temperature-sensing models using fiber optic technology and can facilitate benchmarking against other experimental or synthetic datasets. Finally, an implementation is presented for utilizing the dataset in a deep learning interrogation scheme.

Suggested Citation

  • Francisco J. Vélez & Juan D. Arango & Víctor H. Aristizábal & Carlos Trujillo & Jorge A. Herrera-Ramírez, 2025. "Experimental Dataset for Fiber Optic Specklegram Sensing Under Thermal Conditions and Use in a Deep Learning Interrogation Scheme," Data, MDPI, vol. 10(4), pages 1-8, March.
    • Handle: RePEc:gam:jdataj:v:10:y:2025:i:4:p:44-:d:1620706
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