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A classification multilayer perceptron was applied to train and grasp the fingerprint features of Rayleigh scattering spectrum in the optical fiber. The training set was constructed by moving the reference spectrum and adding the supplementary spectrum. Strain measurement was employed to verify the feasibility of the method. Compared with the traditional cross-correlation algorithm, the multilayer perceptron achieves a larger measurement range, better measurement accuracy, and is less time-consuming. To our knowledge, this is the first time that machine learning has been introduced into an optical frequency domain reflectometry system. Such thoughts and results would bring new knowledge and optimization to the optical frequency domain reflectometer system.<\/jats:p>","DOI":"10.3390\/s23063165","type":"journal-article","created":{"date-parts":[[2023,3,16]],"date-time":"2023-03-16T03:14:35Z","timestamp":1678936475000},"page":"3165","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["Optical Frequency Domain Reflectometry Based on Multilayer Perceptron"],"prefix":"10.3390","volume":"23","author":[{"given":"Guolu","family":"Yin","sequence":"first","affiliation":[{"name":"Key Laboratory of Optoelectronic Technology & Systems (Ministry of Education), Chongqing University, Chongqing 400044, China"},{"name":"State Key Laboratory of Coal Mine Disaster Dynamics and Control, Chongqing University, Chongqing 400044, China"}]},{"given":"Zhaohao","family":"Zhu","sequence":"additional","affiliation":[{"name":"School of Microelectronics & Communication Engineering, Chongqing University, Chongqing 400044, China"}]},{"given":"Min","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Microelectronics & Communication Engineering, Chongqing University, Chongqing 400044, China"}]},{"given":"Yu","family":"Wang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Optoelectronic Technology & Systems (Ministry of Education), Chongqing University, Chongqing 400044, China"}]},{"given":"Kaijun","family":"Liu","sequence":"additional","affiliation":[{"name":"Key Laboratory of Optoelectronic Technology & Systems (Ministry of Education), Chongqing University, Chongqing 400044, China"}]},{"given":"Kuanglu","family":"Yu","sequence":"additional","affiliation":[{"name":"Institute of Information Science, School of Computer and Information Technology, Beijing Jiaotong University, Beijing 100044, China"},{"name":"Beijing Key Laboratory of Advanced Information Science and Network Technology, Beijing 100044, China"}]},{"given":"Tao","family":"Zhu","sequence":"additional","affiliation":[{"name":"Key Laboratory of Optoelectronic Technology & Systems (Ministry of Education), Chongqing University, Chongqing 400044, China"},{"name":"State Key Laboratory of Coal Mine Disaster Dynamics and Control, Chongqing University, Chongqing 400044, China"}]}],"member":"1968","published-online":{"date-parts":[[2023,3,16]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"693","DOI":"10.1063\/1.92872","article-title":"Optical frequency-domain reflectometry in single-mode fiber","volume":"39","author":"Eickhoff","year":"1981","journal-title":"Appl. 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Express"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"396","DOI":"10.1364\/OE.475715","article-title":"Optical frequency domain reflectometry shape sensing using an extruded optical fiber triplet for intra-arterial guidance","volume":"31","author":"Francoeur","year":"2023","journal-title":"Opt. Express"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"6624","DOI":"10.1109\/JLT.2021.3100854","article-title":"Shape sensing using two outer cores of multicore fiber and optical frequency domain reflectometer","volume":"39","author":"Meng","year":"2021","journal-title":"J. Light. Technol."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"6800809","DOI":"10.1109\/JPHOT.2021.3098300","article-title":"Demonstration of large curvature radius shape sensing using optical frequency domain reflectometry in multi-core fibers","volume":"13","author":"Chen","year":"2021","journal-title":"IEEE Photonics J."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"22074","DOI":"10.1364\/OE.27.022074","article-title":"Distributed fiber optics 3D shape sensing by means of high scattering NP-doped fibers simultaneous spatial multiplexing","volume":"27","author":"Beisenova","year":"2019","journal-title":"Opt. Express"},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Katrenova, Z., Alisherov, S., Abdol, T., Yergibay, M., Kappassov, Z., Tosi, D., and Molardi, C. (2022). Investigation of high-resolution distributed fiber sensing system embedded in flexible silicone carpet for 2D pressure mapping. 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Express"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"618","DOI":"10.1016\/j.measurement.2019.07.010","article-title":"A network theory for BOTDA measurement of deformations of geotechnical structures and error analysis","volume":"146","author":"Feng","year":"2019","journal-title":"Measurement"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1016\/j.optcom.2019.124418","article-title":"Temperature extraction for Brillouin optical fiber sensing system based on extreme learning machine","volume":"453","author":"Wang","year":"2019","journal-title":"Opt. Commun."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"102860","DOI":"10.1016\/j.yofte.2022.102860","article-title":"Improving the Brillouin frequency shift measurement resolution in the Brillouin optical time domain reflectometry (BOTDR) fiber sensor by artificial neural network (ANN)","volume":"70","author":"Almoosa","year":"2022","journal-title":"Opt. Fiber Technol."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"4304","DOI":"10.1007\/s12205-021-1805-z","article-title":"Structural Deformation Sensing Based on Distributed Optical Fiber Monitoring Technology and Neural Network","volume":"25","author":"Hou","year":"2021","journal-title":"KSCE J. Civ. Eng."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"5764","DOI":"10.1109\/JLT.2018.2878450","article-title":"Distributed vibration sensor based on space-division multiplexed reflectometer and interferometer in multicore fiber","volume":"36","author":"Zhao","year":"2018","journal-title":"J. Light. Technol."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"143473","DOI":"10.1109\/ACCESS.2021.3121767","article-title":"A recognition method for multi-radial-distance event of Phi-OTDR system based on CNN","volume":"9","author":"Shi","year":"2021","journal-title":"IEEE Access"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"170380","DOI":"10.1016\/j.ijleo.2022.170380","article-title":"\u03c6-OTDR pattern recognition based on CNN-LSTM","volume":"272","author":"Wang","year":"2023","journal-title":"Optik"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"133","DOI":"10.1364\/AO.477642","article-title":"Single and composite disturbance event recognition based on the DBN-GRU network in \u03c6-OTDR","volume":"62","author":"Liu","year":"2023","journal-title":"Appl. Opt."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"34453","DOI":"10.1364\/OE.469342","article-title":"Integrated denoising and extraction of both temperature and strain based on a single CNN framework for a BOTDA sensing system","volume":"30","author":"Yang","year":"2022","journal-title":"Opt. Express"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"262","DOI":"10.1109\/JLT.2021.3117284","article-title":"Deep learning enhanced Long-range fast BOTDA for vibration measurement","volume":"40","author":"Zheng","year":"2022","journal-title":"J. Light. Technol."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"4549","DOI":"10.1364\/OE.27.004549","article-title":"Back propagation neutral network based signal acquisition for Brillouin distributed optical fiber sensors","volume":"27","author":"Cao","year":"2019","journal-title":"Opt. Express"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"31210","DOI":"10.1364\/OE.25.031210","article-title":"Support vector machine assisted BOTDA utilizing combined Brillouin gain and phase information for enhanced sensing accuracy","volume":"25","author":"Wu","year":"2017","journal-title":"Opt. Express"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"6871","DOI":"10.1109\/JSEN.2022.3152254","article-title":"Enhanced neural network implementation for yemperature profile extraction in distributed brillouin scattering-based sensors","volume":"22","author":"Madaschi","year":"2022","journal-title":"IEEE Sens. J."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"3397","DOI":"10.1109\/JSEN.2021.3139321","article-title":"Performance enhancement of BOTDA based on the image super-resolution reconstruction","volume":"22","author":"Hu","year":"2022","journal-title":"IEEE Sens. J."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"13942","DOI":"10.1364\/OE.451877","article-title":"Wavelet convolutional neural network for robust and fast temperature measurements in Brillouin optical time domain reflectometry","volume":"30","author":"Chen","year":"2022","journal-title":"Opt. Express"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"119448","DOI":"10.1109\/ACCESS.2020.3004207","article-title":"A novel DAS signal recognition method based on spatiotemporal information extraction with 1DCNNs-BiLSTM network","volume":"8","author":"Wu","year":"2020","journal-title":"IEEE Access"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"19666","DOI":"10.1109\/JSEN.2022.3202963","article-title":"An ameliorated denoising scheme based on deep learning for phi-OTDR system with 41-km detection range","volume":"22","author":"Li","year":"2022","journal-title":"IEEE Sens. J."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"5951","DOI":"10.1364\/AO.458736","article-title":"Temporal convolution network with a dual attention mechanism for phi-OTDR event classification","volume":"61","author":"Tian","year":"2022","journal-title":"Appl. Opt."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"31232","DOI":"10.1364\/OE.468779","article-title":"Event recognition method based on dual-augmentation for an Phi-OTDR system with a few training samples","volume":"30","author":"Shi","year":"2022","journal-title":"Opt. Express"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"9293","DOI":"10.1109\/JSTARS.2022.3216590","article-title":"Spatial-spectral involution MLP network for hyperspectral image classification","volume":"15","author":"Shao","year":"2022","journal-title":"IEEE J. Sel. Top. Appl. Earth Observ. Remote Sens."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"644","DOI":"10.1049\/cvi2.12131","article-title":"Sparse point-voxel aggregation network for efficient point cloud semantic segmentation","volume":"16","author":"Fang","year":"2022","journal-title":"IET Comput. Vis."},{"key":"ref_39","first-page":"1991","article-title":"Modeling and prediction using an artificial neural network to study the impact of foreign direct investment on the growth rate \/ a case study of the State of Qatar","volume":"25","author":"Heydari","year":"2022","journal-title":"J. Stat. Manag. Syst."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"4843","DOI":"10.1109\/JLT.2020.2993228","article-title":"Distributed characterization of few-mode fibers based on optical frequency domain reflectometry","volume":"38","author":"Veronese","year":"2020","journal-title":"J. Light. 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