Recognition and Localization of FBG Temperature Sensing Based on Combined CDAE and 1-DCNN

In quasi-distributed fiber Bragg grating (FBG) temperature sensor networks, noise and spectral distortions affect the demodulation accuracy of the fiber gratings. To address this issue, we construct a sensor network using spectral encoding and propose a novel approach that combines convolutional den...

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Veröffentlicht in:	IEEE sensors journal Jg. 24; H. 7; S. 10125 - 10137
Hauptverfasser:	Jiang, Hong, Tang, Rui, Wang, Chenyang, Zhao, Yihan, Li, Hao
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 01.04.2024 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	1-D convolutional neural network (1-DCNN) Accuracy Artificial neural networks Bragg gratings convolutional denoising autoencoder (CDAE) Demodulation fiber Bragg grating (FBG) Fiber gratings Goodness of fit Location awareness Machine learning Noise reduction Optical fiber sensors Recognition Reflection Root-mean-square errors Sensors Spectra spectral distortions Temperature temperature sensor networks Temperature sensors
ISSN:	1530-437X, 1558-1748
Online-Zugang:	Volltext
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