Laser & Optoelectronics Progress, Volume. 58, Issue 13, 1306022(2021)
Advances of Machine Learning in Brillouin Optical Time Domain Analysis Sensing Systems for Temperature Extraction
Fig. 1. Diagram of optical fiber temperature sensing system based on BOTDA[9]
Fig. 2. Principle of using SVM to extract temperature information of BGS[29]
Fig. 3. Schematic diagram of training and testing steps required to extract temperature information with optimized SVM algorithm[31]
Fig. 4. Typical ANN structure diagram[28]
Fig. 5. Schematic diagram of training and testing steps required to extract temperature information with ANN[28]
Fig. 6. Structure of BP neural network[35]
Fig. 7. Schematic diagram of training and testing steps required to extract temperature information with BP neural network[35]
Fig. 8. Structure of DNN with 2 autoencoder hidden layers[37]
Fig. 9. Principle of using DNN for simultaneous temperature and strain measurement[38]
Fig. 10. Structure of DnCNN[39]
Fig. 11. Structure of ELM with three layers[41]
Fig. 12. Structure of ESN[41]
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Zhilong Li, Weihua Zhang, Yimin Wang, Yufeng Zhang, Bin Luo, Hongna Zhu. Advances of Machine Learning in Brillouin Optical Time Domain Analysis Sensing Systems for Temperature Extraction[J]. Laser & Optoelectronics Progress, 2021, 58(13): 1306022
Category: Fiber Optics and Optical Communications
Received: Jan. 22, 2021
Accepted: Mar. 22, 2021
Published Online: Jul. 5, 2021
The Author Email: Zhang Weihua (whzhang@nudt.edu.cn), Zhu Hongna (hnzhu@swjtu.edu.cn)