Pattern-recognition-based dual-point fiber temperature sensor using a reliable synthetic database
[EN] We propose to use the nonlinearity in wavelength sweeping of a distributed feedback (DFB) diode laser to generate a reliable synthetic database implemented in a pattern recognition-based fiber sensor. Firstly, the experimentally extracted wavelength-sweeping nonlinearity permits obtaining the t...
| Autores: | , , , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2024 |
| País: | España |
| Institución: | Universitat Politècnica de València (UPV) |
| Repositorio: | RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia |
| Idioma: | inglés |
| OAI Identifier: | oai:riunet.upv.es:10251/220657 |
| Acceso en línea: | https://riunet.upv.es/handle/10251/220657 |
| Access Level: | acceso abierto |
| Palabra clave: | Temperature fiber sensor Fiber interferometer Nonlinear effect Pattern recognition |
| Sumario: | [EN] We propose to use the nonlinearity in wavelength sweeping of a distributed feedback (DFB) diode laser to generate a reliable synthetic database implemented in a pattern recognition-based fiber sensor. Firstly, the experimentally extracted wavelength-sweeping nonlinearity permits obtaining the time-varying tuning rate along the sweeping period. Secondly, this tuning rate is used to simulate a two-point interferometric sensing system under a complete set of temperature variations to generate a reliable synthetic database used to train a pattern recognition algorithm. Thirdly, the trained algorithm is successfully implemented for correctly identifying the experimental sensing signals of a dual-point temperature sensor. In fiber sensor systems employing machine learning algorithms, a huge amount of experimental data is required to ensure accurate pattern classification, which becomes a challenging task. The methodology for generating a reliable synthetic database provides time and resource savings in the lab, without compromising the accuracy of the results. A standard DFB diode laser, wavelength tuned over a few tens of pico-meters, is used as an optical source, and a PIN photodetector is used as an optical detector. A description of the wavelength-nonlinearity extraction approach, a mathematical model of the interferometric fiber sensor, and experimental results confirming the effectiveness of the proposed sensing system are reported. Also, classification results using a database generated without including the nonlinearity effect are presented to highlight the importance of considering this nonlinearity. |
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