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dc.contributor.authorDzhala, Roman-
dc.contributor.authorDzhala, Vasyl’-
dc.contributor.authorHoron, Bohdan-
dc.contributor.authorSenyuk, Oleh-
dc.contributor.authorVerbenets’, Bohdan-
dc.date.accessioned2019-10-23T15:06:06Z-
dc.date.available2019-10-23T15:06:06Z-
dc.date.issued2019-09-16-
dc.identifier.citationDzhala R., Dzhala V., Horon B., Senyuk O., Verbenets’ B. Information Technology of Surveys and Diagnostics of Underground Pipelines // 2019 XIth International Scientific and Practical Conference on Electronics and Information Technologies (ELIT), September 16–18, 2019, Lviv, Ukraine. P. 214–218.uk_UA
dc.identifier.isbn978-1-7281-3561-8-
dc.identifier.urihttp://elartu.tntu.edu.ua/handle/lib/29030-
dc.description.abstractThe problems of inspections, nondestructive testing, and diagnostics of underground pipelines from the standpoint of the structure and functioning of modern cyber-physical systems are discussed. Method and apparatus for contactless measurement of currents with memory and automatic computer processing of results improve efficiency and information of testing to ensure the reliability and extension of trouble-free operation of pipelines.uk_UA
dc.format.extent214–218-
dc.language.isoenuk_UA
dc.titleInformation Technology of Surveys and Diagnostics of Underground Pipelinesuk_UA
dc.typeConference Abstractuk_UA
dc.coverage.placenameLviv, Ukraineuk_UA
dc.relation.references[1] R. M. Dzhala, “Bases of inspection and control of corrosion state of underground pipelines”, Fracture mechanics and strength of materials: Reference manual, ed.-in-chief V.V. Panasyuk, vol. 11: Strength and durability of oil and gas pipelines and storage tanks, ed. H. M. Nykyforchyn, Chapter 6. Lviv: Spolom, 2009, pp. 143–184 [in Ukrainian].uk_UA
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dc.relation.references[3] R. M. Dzhala (ed), V. R. Dzhala, I. B. Ivasiv, V. G. Rybachuk, and V. M. Uchanin, “Electrophysical methods for nondestructive testing of defects in structural elements”, Technical diagnostics of materials and structures: Reference manual, ed.-in-chief Z.T. Nazarchuk, vol. 4. Lviv: Prostir-M, 2018 [in Ukrainian].uk_UA
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dc.relation.references[7] L. Dikmarova, V. Nichoga, and P. Dub, “Informative parameters of the external field of underground pipeline in problems of remote testing of corrosion protection,” IEEE Trans. Instrum. Meas., vol. 51, pp. 92–95, February 2002.uk_UA
dc.relation.references[8] L. Dikmarova, V. Nichoga, and P. Dub, “On a possibility of determi- nation of underground pipeline corrosion state by contactless methods”, Proc. 2nd IEEE Int. Workshop on Intelligent Data Acquisition and Advanced Comput. Systems: Technology and Applications, IDAACS’2003, Lviv, Ukraine, pp. 164–167, September 2003.uk_UA
dc.relation.references[9] R. M. Dzhala, B. Ya. Verbenets', M. I. Melnyk, A. B. Mytsyk, R. S. Savula, and O. M. Seмеnyuk, “New methods for the corrosion monitoring of underground pipelines according to the measurement of currents and potentials,” Materials Sci., vol. 52, pp. 732–741, March 2017.uk_UA
dc.relation.references[10] B. Milesevic, B. Filipovic-Grcic, and T. Radosevic, “Analysis of low frequency electromagnetic fields and calculation of induced voltages to an underground pipeline,” Proc. 3rd Int. Youth Conf. on Energetics (IYCE), Leiria, Portugal, vol. 1, pp. 1–7, July 2011.uk_UA
dc.relation.references[11] M. M. Din, N. Ithnin, A. M. Zain, N. M. Noor, M. M. Siraj, and R. M. Rasol, “An artificial neural network modeling for pipeline corrosion growth prediction,” ARPN J. Eng. Appl. Sci., vol. 10, Issue 2, pp. 512–519, 2015.uk_UA
dc.relation.references[12] V. Lozovan, R. Dzhala, R. Skrynkovskyy, and V. Yuzevych, “Detection of specific features in the functioning of a system for the anti-corrosion protection of underground pipelines at oil and gas enterprises using neural networks,” Eastern-European Journal of Enterprise Technologies, vol. 1, No 5 (97), pp. 20–27. 2019.uk_UA
dc.relation.references[13] V. Lozovan, R. Skrynkovskyy, V. Yuzevych, M. Yasinskyi, and G. Pawlowski, “Forming the toolset for development of a system to control quality of operation of underground pipelines by oil and gas enterprises with the use of neural networks,” Eastern-European Journal of Enterprise Technologies, vol. 2, No 5 (98). pp. 41–48. 2019.uk_UA
dc.relation.references[14] L.Yuzevych, R. Skrynkovskyy, V. Yuzevych, V. Lozovan, G. Pawlowski, M. Yasinskyi, and I. Ogirko, “Improving the diagnostics of underground pipelines at oil-and-gas enterprises based on determining hydrogen exponent (PH) of the soil media applying neural networks,” Eastern-European Journal of Enterprise Technologies, vol. 4, No 5 (100). pp. 56–64. 2019.uk_UA
dc.contributor.affiliationKarpenko Physico-Mechanical Institute of the NAS of Ukraine (Lviv, Ukraine)uk_UA
dc.citation.conference2019 XIth International Scientific and Practical Conference on Electronics and Information Technologies (ELIT)-
dc.coverage.countryUAuk_UA
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