Multi-Sensor Temperature and Humidity Measuring System for Technological Process of Organic Livestock Waste Microwave Treatment Monitoring

Насыбуллин, А. Р.; Morozov, Gennady A.; Anfinogentov, Vladimir; Lipatnikov, K. A.; Smirnov, S. V.

doi:10.1109/weconf51603.2021.9470606

Cited by 3 publications

(1 citation statement)

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“…Microwave photonic techniques have applications in various fields including telecommunications [4], radar systems [5,6], wireless communications, measurement technology [7,8] and fiber-optic sensing [9][10][11]. The use of microwave photonic methods in fiber-optic sensing allows not only to significantly reduce the cost of interrogation equipment but at the same time to increase both the speed and accuracy of measurements [10][11][12][13].…”

Section: Introductionmentioning

confidence: 99%

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

Makarov,

Qaid,

Al Hussein

et al. 2024

Optics

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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 generator realizing a microwave photonic approach. Firstly, modelling of the reflection spectrum of a Fabry–Perot interferometer is implemented. Secondly, probing of the obtained spectrum using a comb-generator model is performed. The resulting electrical signal of the photodetector is processed and is used to create a sample for artificial neural network training aimed at temperature detection. It is demonstrated that the artificial neural network implementation can predict temperature variations with an accuracy equal to 0.018 °C in the range from −10 to +10 °C and 0.147 in the range from −15 to +15 °C.

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