2023
DOI: 10.1016/j.yofte.2023.103356
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A deep learning algorithm ADPNet for strain and temperature decoupling of fiber bragg gratings

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Cited by 3 publications
(1 citation statement)
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“…The temperature compensation method [168,169] is used to insulate one of the sensor structures from strain by encapsulation so that it only provides temperature information that can be used to compensate the temperature influence on the other structure. In addition, machine learning [170][171][172] has also been used to solve the problem of cross-sensitivity, and this method can achieve the decoupling of temperature and strain with a single sensor structure, reducing the cost and complexity of the sensor system. However, its limitation is that the demodulation accuracy is not high and needs more computational power.…”
Section: Cross Sensitivity Between Temperature and Strainmentioning
confidence: 99%
“…The temperature compensation method [168,169] is used to insulate one of the sensor structures from strain by encapsulation so that it only provides temperature information that can be used to compensate the temperature influence on the other structure. In addition, machine learning [170][171][172] has also been used to solve the problem of cross-sensitivity, and this method can achieve the decoupling of temperature and strain with a single sensor structure, reducing the cost and complexity of the sensor system. However, its limitation is that the demodulation accuracy is not high and needs more computational power.…”
Section: Cross Sensitivity Between Temperature and Strainmentioning
confidence: 99%