Enhancing Microwave Photonic Interrogation Accuracy for Fiber-Optic Temperature Sensors via Artificial Neural Network Integration

In this paper, an application of an artificial neural network algorithm is proposed to enhance the accuracy of temperature measurement using a fiber-optic sensor based on a Fabry–Perot interferometer (FPI). It is assumed that the interrogation of the FPI is carried out using an optical comb generato...

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Bibliografiska uppgifter

Huvudupphov:	Roman Makarov, Mohammed R. T. M. Qaid, Alaa N. Al Hussein, Bulat Valeev, Timur Agliullin, Vladimir Anfinogentov, Airat Sakhabutdinov
Materialtyp:	Artigo
Språk:	Inglês
Utgiven:	MDPI AG 2024-04-01
Serie:	Optics
Ämnen:	fiber-optic sensors microwave photonics convolutional neural networks fuzzy logic algorithms optical frequency comb Fabry–Perot interferometer
Länkar:	https://www.mdpi.com/2673-3269/5/2/16
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