{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,8]],"date-time":"2026-01-08T19:17:09Z","timestamp":1767899829433,"version":"3.49.0"},"reference-count":53,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2023,5,22]],"date-time":"2023-05-22T00:00:00Z","timestamp":1684713600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100006769","name":"Russian Science Foundation","doi-asserted-by":"publisher","award":["22-79-00225"],"award-info":[{"award-number":["22-79-00225"]}],"id":[{"id":"10.13039\/501100006769","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>The paper presents the application of a phase-sensitive optical time-domain reflectometer (phi-OTDR) in the field of urban infrastructure monitoring. In particular, the branched structure of the urban network of telecommunication wells. The encountered tasks and difficulties are described. The possibilities of usage are substantiated, and the numerical values of the event quality classification algorithms applied to experimental data are calculated using machine learning methods. Among the considered methods, the best results were shown by convolutional neural networks, with a probability of correct classification as high as 98.55%.<\/jats:p>","DOI":"10.3390\/s23104978","type":"journal-article","created":{"date-parts":[[2023,5,23]],"date-time":"2023-05-23T02:02:27Z","timestamp":1684807347000},"page":"4978","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":15,"title":["Fiber-Optic Telecommunication Network Wells Monitoring by Phase-Sensitive Optical Time-Domain Reflectometer with Disturbance Recognition"],"prefix":"10.3390","volume":"23","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6772-1572","authenticated-orcid":false,"given":"Andrey A.","family":"Zhirnov","sequence":"first","affiliation":[{"name":"Bauman Moscow State Technical University, 2-nd Baumanskaya 5-1, 105005 Moscow, Russia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"German Y.","family":"Chesnokov","sequence":"additional","affiliation":[{"name":"Department of Applied Mathematics, MIEM, National Research University Higher School of Economics, 123458 Moscow, Russia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Konstantin V.","family":"Stepanov","sequence":"additional","affiliation":[{"name":"Bauman Moscow State Technical University, 2-nd Baumanskaya 5-1, 105005 Moscow, Russia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tatyana V.","family":"Gritsenko","sequence":"additional","affiliation":[{"name":"Bauman Moscow State Technical University, 2-nd Baumanskaya 5-1, 105005 Moscow, Russia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Roman I.","family":"Khan","sequence":"additional","affiliation":[{"name":"Bauman Moscow State Technical University, 2-nd Baumanskaya 5-1, 105005 Moscow, Russia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kirill I.","family":"Koshelev","sequence":"additional","affiliation":[{"name":"Bauman Moscow State Technical University, 2-nd Baumanskaya 5-1, 105005 Moscow, Russia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0302-5687","authenticated-orcid":false,"given":"Anton O.","family":"Chernutsky","sequence":"additional","affiliation":[{"name":"Bauman Moscow State Technical University, 2-nd Baumanskaya 5-1, 105005 Moscow, Russia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Cesare","family":"Svelto","sequence":"additional","affiliation":[{"name":"Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, 20133 Milan, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Alexey B.","family":"Pnev","sequence":"additional","affiliation":[{"name":"Bauman Moscow State Technical University, 2-nd Baumanskaya 5-1, 105005 Moscow, Russia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Olga V.","family":"Valba","sequence":"additional","affiliation":[{"name":"Department of Applied Mathematics, MIEM, National Research University Higher School of Economics, 123458 Moscow, Russia"},{"name":"Laboratory of Complex Networks, Brain and Consciousness Research Center, 119991 Moscow, Russia"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2023,5,22]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1365","DOI":"10.1002\/j.1538-7305.1980.tb03369.x","article-title":"High-Speed Digital Lightwave Communication Using LEDs and PIN Photodiodes at 1.3 \u03bcm","volume":"59","author":"Gloge","year":"1980","journal-title":"Bell Syst. Tech. J."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1451","DOI":"10.1109\/JSAC.1986.1146489","article-title":"High-speed CMI optical intraoffice transmission system: Design and performance","volume":"4","author":"Hagishima","year":"1986","journal-title":"IEEE J. Sel. Areas Commun."},{"key":"ref_3","unstructured":"Itoh, T., Shimada, S., and Nakagawa, \u039a. (1986, January 22\u201325). Gigabit\/s optical fiber transmission systems\u2014Today and tomorrow. Proceedings of the International Communications Conference (ICC), Toronto, ON, Canada."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"95","DOI":"10.1002\/j.1538-7305.1987.tb00478.x","article-title":"Terrestrial lightwave systems","volume":"66","author":"Sanferrare","year":"1987","journal-title":"AT&T Tech. J."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"2025","DOI":"10.1109\/26.61485","article-title":"A survey of light-weight transport protocols for high-speed networks","volume":"38","author":"Doeringer","year":"1990","journal-title":"IEEE Trans. Commun."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"188","DOI":"10.1002\/bltj.2214","article-title":"The evolution of optical systems: Optics everywhere","volume":"5","author":"Alferness","year":"2000","journal-title":"Bell Labs Tech. J."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"123","DOI":"10.1126\/science.6422554","article-title":"Fiber-optic sensors for biomedical applications","volume":"224","author":"Peterson","year":"1984","journal-title":"Science"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1193","DOI":"10.1109\/50.400697","article-title":"Historical review of microbend fiber-optic sensors","volume":"13","author":"Berthold","year":"1995","journal-title":"J. Light. Technol."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"40","DOI":"10.1016\/S0924-4247(99)00368-4","article-title":"Fiber optic sensor technology: An overview","volume":"82","author":"Grattan","year":"2000","journal-title":"Sens. Actuators A Phys."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Gorshkov, B.G., Y\u00fcksel, K., Fotiadi, A.A., Wuilpart, M., Korobko, D.A., Zhirnov, A.A., Stepanov, K.V., Turov, A.T., Konstantinov, Y.A., and Lobach, I.A. (2022). Scientific Applications of Distributed Acoustic Sensing: State-of-the-Art Review and Perspective. Sensors, 22.","DOI":"10.3390\/s22031033"},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Wang, Z., Lu, B., Ye, Q., and Cai, H. (2020). Recent Progress in Distributed Fiber Acoustic Sensing with \u03a6-OTDR. Sensors, 20.","DOI":"10.3390\/s20226594"},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Barrias, A., Casas, J.R., and Villalba, S. (2016). A Review of Distributed Optical Fiber Sensors for Civil Engineering Applications. Sensors, 16.","DOI":"10.3390\/s16050748"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"687","DOI":"10.1134\/S0020441222050268","article-title":"State-of-the-Art Methods for Determining the Frequency Shift of Brillouin Scattering in Fiber-Optic Metrology and Sensing (Review)","volume":"65","author":"Krivosheev","year":"2022","journal-title":"Instrum. Exp. Tech."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"249","DOI":"10.18178\/ijeetc.11.4.249-261","article-title":"Metrological Applications of Optical Reflectometry: A Review","volume":"11","author":"Konstantinov","year":"2022","journal-title":"IJEETC"},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Agrawal, G.P. (2011). Fiber-Optic Communication Systems, John Wiley & Sons.","DOI":"10.1002\/9780470918524"},{"key":"ref_16","unstructured":"Taylor, H.F., and Lee, C.E. (1993). Apparatus and Method for Fiber Optic Intrusion Sensing. (No 5,194,847 A), U.S. Patent."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"1315","DOI":"10.1364\/AO.33.001315","article-title":"Fiber-optic pressure sensors for internal combustion engines","volume":"33","author":"Atkins","year":"1994","journal-title":"Appl. Opt."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"2081","DOI":"10.1109\/JLT.2005.849924","article-title":"Distributed fiber-optic intrusion sensor system","volume":"23","author":"Juarez","year":"2005","journal-title":"J. Lightwave Technol."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"134","DOI":"10.1117\/12.484911","article-title":"Distributed fiber optic pressure\/seismic sensor for low-cost monitoring of long perimeters","volume":"5090","author":"Choi","year":"2003","journal-title":"Proc. SPIE"},{"key":"ref_20","first-page":"692","article-title":"Distributed fiber optic intrusion sensor system for monitoring long perimeters","volume":"Volume 5778","author":"Juarez","year":"2005","journal-title":"Sensors, and Command, Control, Communications, and Intelligence (C3I) Technologies for Homeland Security and Homeland Defense IV"},{"key":"ref_21","unstructured":"Lee, M., and Taylor, H.F. Optical Fiber Sensors, Optica Publishing Group."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Stepanov, K.V., Zhirnov, A.A., Chernutsky, A.O., Koshelev, K.I., Pnev, A.B., Lopunov, A.I., and Butov, O.V. (2020). The Sensitivity Improvement Characterization of Distributed Strain Sensors Due to Weak Fiber Bragg Gratings. Sensors, 20.","DOI":"10.3390\/s20226431"},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Stepanov, K.V., Zhirnov, A.A., Chernutsky, A.O., Choban, T.V., Pnev, A.B., Lopunov, A.I., and Butov, O.V. (2020, January 2\u20136). Spatial Resolution Improvement for phi-OTDR Sensors via Weak Fiber Bragg Gratings. Proceedings of the 2020 International Conference Laser Optics (ICLO), St. Petersburg, Russia.","DOI":"10.1109\/ICLO48556.2020.9285505"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"962003","DOI":"10.1117\/12.2192682","article-title":"The performance limit of \u03a6-OTDR sensing system enhanced with ultra-weak fiber Bragg grating array","volume":"9620","author":"Xia","year":"2015","journal-title":"Proc. SPIE"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"4775","DOI":"10.1109\/JLT.2015.2477243","article-title":"Improved \u03a6-OTDR sensing system for high-precision dynamic strain measurement based on ultra-weak fiber bragg grating array","volume":"33","author":"Zhu","year":"2015","journal-title":"J. Lightwave Technol."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"17437","DOI":"10.1364\/OE.26.017437","article-title":"Simultaneous distributed static and dynamic sensing based on ultra-short fiber Bragg gratings","volume":"26","author":"Li","year":"2018","journal-title":"Opt. Express"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"677","DOI":"10.1109\/LPT.2018.2811411","article-title":"Interrogation of ultra-weak FBG array using double-pulse and heterodyne detection","volume":"30","author":"Liu","year":"2018","journal-title":"IEEE Photon. Technol. Lett."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Popov, S.M., Butov, O.V., Kolosovskiy, A.O., Voloshin, V.V., Vorob\u2019ev, I.L., Vyatkin, M.Y., Fotiadi, A.A., and Chamorovskiy, Y.K. (2017, January 22\u201325). Optical fibres with arrays of FBG: Properties and application. Proceedings of the 2017 Progress in Electromagnetics Research Symposium\u2013Spring (PIERS), St. Petersburg, Russia.","DOI":"10.1109\/PIERS.2017.8261997"},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Liu, T., Li, H., Ai, F., Wang, J., Fan, C., Luo, Y., Yan, Z., Liu, D., and Sun, Q. (2019, January 3\u20137). Ultra-high Resolution Distributed Strain Sensing based on Phase-OTDR. Proceedings of the 2019 Optical Fiber Communications Conference and Exhibition (OFC), San Diego, CA, USA.","DOI":"10.1364\/OFC.2019.Th2A.16"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"1499","DOI":"10.1109\/JQE.1982.1071408","article-title":"Single-mode fiber OTDR: Experiment and theory","volume":"18","author":"Philen","year":"2003","journal-title":"IEEE J. Quant. Elect"},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Madsen, C.K., Bae, T., and Snider, T. (2007, January 9\u201312). Intruder signature analysis from a phase-sensitive distributed fiber-optic perimeter sensor. Proceedings of the Fiber Optic Sensors and Applications V 2007, Boston, MA, USA.","DOI":"10.1117\/12.735244"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"6802610","DOI":"10.1109\/JPHOT.2017.2700894","article-title":"SNR enhancement in phase-sensitive OTDR with adaptive 2D bilateral filtering algorithm","volume":"9","author":"He","year":"2017","journal-title":"IEEE Photonics J."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"2099","DOI":"10.1016\/j.ijleo.2013.10.036","article-title":"Localization mechanisms and location methods of the disturbance sensor based on phase-sensitive OTDR","volume":"125","author":"Li","year":"2014","journal-title":"Optik"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"1061","DOI":"10.1109\/JSEN.2014.2360559","article-title":"An Improved Denoising Method in RDTS Based on Wavelet Transform Modulus Maxima","volume":"15","author":"Wang","year":"2014","journal-title":"IEEE Sens. J."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"7235","DOI":"10.1016\/j.ijleo.2014.07.128","article-title":"Fiber-optic distributed sensor based on phase-sensitive OTDR and wavelet packet transform for multiple disturbances location","volume":"125","author":"Lin","year":"2014","journal-title":"Optik"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"305","DOI":"10.1007\/s13320-017-0360-1","article-title":"Feature extraction and identification in distributed optical-fiber vibration sensing system for oil pipeline safety monitoring","volume":"7","author":"Wu","year":"2017","journal-title":"Photonic Sens."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"15179","DOI":"10.3390\/s150715179","article-title":"Recognition of a Phase-Sensitivity OTDR Sensing System Based on Morphologic Feature Extraction","volume":"15","author":"Sun","year":"2015","journal-title":"Sensors"},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Makarenko, A.V. (2016, January 13\u201316). Deep Learning Algorithms for Signal Recognition in long Perimeter Monitoring Distributed Fiber Optic Sensors. Proceedings of the 2016 IEEE 26th International Workshop on Machine Learning for Signal Processing (MLSP), Vietri sul Mare, Italy.","DOI":"10.1109\/MLSP.2016.7738863"},{"key":"ref_39","first-page":"102080","article-title":"Deep learning based multi-threat classification for phase-OTDR fiber optic distributed acoustic sensing applications","volume":"10208","author":"Aktas","year":"2017","journal-title":"SPIE Commer. Sci. Sens. Imaging"},{"key":"ref_40","unstructured":"Zhu, Q.D., Jing, L.Q., and Bi, R.S. Exploration and Improvement of Ostu Threshold Segmentation Algorithm. Proceedings of the 8th World Congress on Intelligent Control and Automation (WCICA), Jinan, China, 7\u20139 July 2010."},{"key":"ref_41","doi-asserted-by":"crossref","unstructured":"Dai, W., Dai, C., Qu, S., Li, J., and Das, S. (2017, January 5\u20139). Very deep convolutional neural networks for raw waveforms. Proceedings of the 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), New Orleans, LA, USA.","DOI":"10.1109\/ICASSP.2017.7952190"},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Turov, A.T., Konstantinov, Y.A., Barkov, F.L., Korobko, D.A., Zolotovskii, I.O., Lopez-Mercado, C.A., and Fotiadi, A.A. (2023). Enhancing the Distributed Acoustic Sensors\u2019 (DAS) Performance by the Simple Noise Reduction Algorithms Sequential Application. Algorithms, 16, Algorithm 16 and Algorithm 217.","DOI":"10.3390\/a16050217"},{"key":"ref_43","unstructured":"Bishop, C.M. (2006). Pattern Recognition and Machine Learning, Springer."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1023\/A:1010933404324","article-title":"Random Forests","volume":"45","author":"Breiman","year":"2001","journal-title":"Mach. Learn."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"367","DOI":"10.1016\/S0167-9473(01)00065-2","article-title":"Stochastic gradient boosting","volume":"38","author":"Friedman","year":"2002","journal-title":"Comput. Stat. Data Anal."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"102","DOI":"10.1007\/978-1-4612-5110-1_9","article-title":"A stochastic approximation method","volume":"22","author":"Robbins","year":"1985","journal-title":"Herbert Robbins Sel. Pap."},{"key":"ref_47","first-page":"2825","article-title":"Scikit-learn: Machine learning in Python","volume":"12","author":"Pedregosa","year":"2011","journal-title":"Mach. Learn."},{"key":"ref_48","doi-asserted-by":"crossref","unstructured":"Chen, T., and Guestrin, C. (2016, January 13\u201317). Xgboost: A scalable tree boosting system. Proceedings of the 22nd ACM Sigkdd International Conference on Knowledge Discovery and Data Mining, San Francisco, CA, USA.","DOI":"10.1145\/2939672.2939785"},{"key":"ref_49","unstructured":"Chollet, F. (2023, February 24). Keras. Available online: https:\/\/keras.io."},{"key":"ref_50","unstructured":"Abadi, M., Agarwal, A., Barham, P., Brevdo, E., Chen, Z., Citro, C., Corrado, G.S., Davis, A., Dean, J., and Devin, M. (2020, February 24). TensorFlow: Large-Scale Machine Learning on Heterogeneous Systems. Available online: https:\/\/www.tensorflow.org\/."},{"key":"ref_51","first-page":"2579","article-title":"Visualizing data using t-SNE","volume":"9","author":"Maaten","year":"2008","journal-title":"J. Mach. Learn. Res."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"79","DOI":"10.1214\/aoms\/1177729694","article-title":"On information and sufficiency","volume":"22","author":"Kullback","year":"1951","journal-title":"Ann. Math. Stat."},{"key":"ref_53","unstructured":"Pandey, R., Khatri, S.K., Singh, N.K., and Verma, P. (2022). Artificial Intelligence and Machine Learning for EDGE Computing, Academic Press."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/23\/10\/4978\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T19:40:14Z","timestamp":1760125214000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/23\/10\/4978"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,5,22]]},"references-count":53,"journal-issue":{"issue":"10","published-online":{"date-parts":[[2023,5]]}},"alternative-id":["s23104978"],"URL":"https:\/\/doi.org\/10.3390\/s23104978","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,5,22]]}}}