tumnigИзвестия высших учебных заведений. Нефть и газOil and Gas Studies0445-01083033-8174Industrial University of Tyumen10.31660/0445-0108-2019-4-122-129tumnig-764Research ArticleПРОЕКТИРОВАНИЕ, СООРУЖЕНИЕ И ЭКСПЛУАТАЦИЯ СИСТЕМ ТРУБОПРОВОДНОГО ТРАНСПОРТАDESIGNING, CONSTRUCTION AND OPERATION OF PIPELINE TRANSPORT SYSTEMОбоснование эффективности использования декомпозиции вибрационного сигнала как метода диагностики подшипников качения нефтяных насосовRationale for the use of vibration signal decomposition as a diagnostic method for rolling bearings of oil pumpsКононовП. С.KononovР. S.

Кононов Павел Сергеевич, студент

Тюмень

Pavel S. Kononov, Student

Tyumen

ОгудоваЕ. В.OgudovaЕ. V.

Огудова Евгения Владимировна, старший преподаватель кафедры транспорта углеводородных ресурсов

Тюмень

Evgenia V. Ogudova, Senior Lecturer at the Department of Transportation of Hydro-carbon Resources

Tyumen

specular@mail.ruТюменский индустриальный университетРоссияIndustrial University of TyumenRussian Federation20192209201904122129Copyright © Кононов П.С., Огудова Е.В., 20192019Кононов П.С., Огудова Е.В.Kononov Р.S., Ogudova Е.V.Данная работа распространяется под лицензией Creative Commons Attribution 4.0.This work is licensed under a Creative Commons Attribution 4.0 License.https://tumnig.tyuiu.ru/jour/article/view/764

На сегодняшний день в условиях длительной эксплуатации и широкого диапазона режимов работы важнейшую роль играют задачи по предотвращению аварий, связанных с отказом отдельных узлов оборудования и насоса в целом. Перспективный метод технической диагностики, описанный в работе, предназначен для выявления подобных дефектов и является актуальным в рассмотрении данной проблематики. Полученные данные свидетельствуют о возможности не только выделения интересующего импульса из сигнала необработанной вибрации, но и идентифицирования типа повреждения на ранних этапах.

Today, the development of new technologies and their application in the oil industry is a key factor in improving the reliability of technological equipment. A promising method of technical diagnostics, described in the article, is intended to identify such defects and is relevant in the consideration of this issue. The data obtained indicate that it is possible not only to isolate the pulse of interest from the signal of the untreated vibration, but also to identify the type of damage in the early stages.  

нефтяной насосдиагностикавибрацияамплитудадекомпозиция сигналаoil pumpdiagnosticsvibrationamplitudesignal decompositionReferencesKarimi H., Nasab H. S. Diagnosis using acoustic emission // World Pumps. – 2012. – Vol. 2012, Issue 1. – Р. 33–37. – Available at: https://doi.org/10.1016/S0262-1762(11)70400-XKarimi H., & Nasab, H. S. (2012). Diagnosis using acoustic emission. World Pumps, (1), pp. 33-37. (In English). Available at: https://doi.org/10.1016/S0262-1762(11)70400-XCentrifugal compressor fault diagnosis based on qualitative simulation and thermal parameters / Y. Lu [et al.] // Mechanical Systems and Signal Processing. – 2016. – Vol. 81. – Р. 259–273. – Available at: https://doi.org/10.1016/j.ymssp.2016.03.018Lu, Y., Wang, F., Jia, M., & Qi, Y. (2016). Centrifugal compressor fault diagnosis based on qualitative simulation and thermal parameters. Mechanical Systems and Signal Processing, 81, pp. 259-273. (In English). Available at: https://doi.org/10.1016/j.ymssp.2016.03.018Wang J., He Q. B., Kong F. R. Multiscale envelope manifold for enhanced fault diagnosis of rotating machines// Mechanical Systems and Signal Processing. – 2015. – Vol. 52–53. – Р. 376–392. – Available at: https://doi.org/10.1016/j.ymssp.2014.07.021Wang, J., He, Q. B., & Kong, F. R. (2015). Multiscale envelope manifold for enhanced fault diagnosis of rotating machines. Mechanical Systems and Signal Processing, 52-53, pp. 376-392. (In English). Available at: https://doi.org/10.1016/j.ymssp.2014.07.021Dybala J. Diagnosing of rolling-element bearings using amplitude level-based decomposition of machine vibration signal // Measurement. – 2018. – Vol. 126. – P. 143–155. – Available at: https://doi.org/10.1016/j.measurement.2018.05.031Dybala, J. (2018). Diagnosing of rolling-element bearings using amplitude level-based decomposition of machine vibration signal. Measurement, 126, pp. 143-155. (In English). Available at: https://doi.org/10.1016/j.measurement.2018.05.031Rotating machine fault diagnosis using empirical mode decomposition / Q. Gao [et al.] // Mechanical Systems and Signal Processing. – 2008. – Vol. 22, Issue 5. – P. 1072–1081. – Availa-ble at: https://doi.org/10.1016/j.ymssp.2007.10.003Gao, Q., Duan, C., Fan, H., & Meng, Q. (2008). Rotating machine fault diagnosis using empirical mode decomposition. Mechanical Systems and Signal Processing, 22(5), pp. 1072-1081. (In English). Available at: https://doi.org/10.1016/j.ymssp.2007.10.003Heng R. B. W., Nor, M. J. M. Statistical analysis of sound and vibration signals for monitoring rolling element bearing condition // Applied Acoustic. – 1998. – Vol. 53, Issue 1–3. – P. 211–226. – Available at: https://doi.org/10.1016/S0003-682X(97)00018-2Heng, R. B. W, & Nor M. J. M. (1998). Statistical analysis of sound and vibration signals for monitoring rolling element bearing condition. Applied Acoustic, 53(1-3), pp. 211-226. (In English). Available at: https://doi.org/10.1016/S0003-682X(97)00018-2Lin J., Zuo M. J. Gearbox fault diagnosis using adaptive wavelet filter // Mechanical Systems and Signal Processing. – 2003. – Vol. 17, Issue 6. – P. 1259–1269. – Available at: https://doi.org/10.1006/mssp.2002.1507Lin, J., & Zuo, M. J. (2003). Gearbox fault diagnosis using adaptive wavelet filter. Mechanical Systems and Signal Processing, 17(6), pp. 1259-1269. (In English). Available at: https://doi.org/10.1006/mssp.2002.1507Барков А. В., Баркова Н. А., Азовцев А. Ю. Мониторинг и диагностика роторных машин по вибрации: учеб. пособие. – СПб.: Издательский центр ГМТУ, 2000. – 158 с.Barkov, A. V., Barkova, N. A., & Azovtsev, A. Yu. (2000). Monitoring i diagnostika rotornykh mashin po vibratsii. Saint Petersburg, GMTU Publ., 158 p. (In Russian).Чуи Ч. Введение в вэйвлеты / Пер. с англ. Я.М. Жилейкина. – М.: Мир, 2001. – 412 с.Chui, Ch. K. (1992). An Introduction to Wavelets. Texas, Academic Press. (In English). Available at: https://www.researchgate.net/publication/231222178_An_Introduction_to_WaveletsРусов В. А. Спектральная вибродиагностика. – Пермь, 1996. – 176 с.Rusov, V. A. (1996). Spektral'naya vibrodiagnostika. Perm, 176 p. (In Russian).Добеши И. Десять лекций по вейвлетам. – Ижевск: НИЦ «Регулярная и хаотическая динамика», 2001. – 464 с.Dobeshi, I. Desyat' lektsiy po veyvletam. (2001). Izhevsk: Regulyarnaya i khaoticheskaya dinamika NITS, 464 p. (In Russian).Костюков В. Н. Ранговый метод виброакустической диагностики и оценки качества машин // Гидропривод и системы управления строительных, тяговых и дорожных машин: межвуз. сб. – Омск: ОмПИ, 1985. – С. 113–124.Kostyukov, V. N. (1985). Rangovyy metod vibroakusticheskoy diagnostiki i otsenki kachestva mashin. Gidroprivod i sistemy upravleniya stroitel'nykh, tyagovykh i dorozhnykh mashin. Omsk: OmPI Publ., pp. 113-124. (In Russian).Пат. № 1280961. РФ МПК Н04В 51/0060/М13/02. № 823505038/06. Способ виброакустической диагностики машин периодического действия и устройство для его осуществ-ления / Костюков В. Н.; заявл. 22.10.82; опубл. 20.08.98, Бюл. 16.Kostyukov, V. N. Sposob vibroakusticheskoy diagnostiki mashin periodicheskogo deystviya i ustroystvo dlya ego osushchestvleniya. Pat. № 1280961. RF MPK N04V 51/0060/M13/02. No 823505038/06. Applied. 22.10.82; Published: 20.08.98, Bull. 16. (In Russian).Barszcz T. Decomposition of Vibration Signals into Deterministic and Nondeterministic Components and its Capabilities of Fault Detection and Identification // International Journal of Applied Mathematics and Computation Since. – 2009. – Vol. 19, Issue 2. – P. 327–335. DOI: 10.2478/v10006-009-0028-0Barszcz, T. (2009). Decomposition of vibration signals into deterministic and nondeter-ministic components and its capabilities of fault detection and identification. International Journal of Applied Mathematics and Computation Since, 19(2), pp. 327-335. (In English). DOI: 10.2478/v10006-009-0028-0Harish Chandra N., Sekhar A. S. Fault detection in rotor bearing systems using time frequency techniques // Mechanical Systems and Signal Processing. – 2016. – Vol. 72–73. – P. 105–133. – Available at: https://doi.org/10.1016/j.ymssp.2015.11.013Harish Chandra, N., & Sekhar, A. S. (2016). Fault detection in rotor bearing systems using time frequency techniques. Mechanical Systems and Signal Processing, 72-73, pp. 105-133. (In English). Available at: https://doi.org/10.1016/j.ymssp.2015.11.013Lv Y., Yuan R., Song G. Multivariate empirical mode decomposition and its application to fault diagnosis of rolling bearing // Mechanical Systems and Signal Processing. – 2016. – Vol. 81. – P. 219–234. – Available at: https://doi.org/10.1016/j.ymssp.2016.03.010Lv, Y., Yuan, R., & Song, G. (2016). Multivariate empirical mode decomposition and its application to fault diagnosis of rolling bearing. Mechanical Systems and Signal Processing, 81, pp. 219-234. (In English). Available at: https://doi.org/10.1016/j.ymssp.2016.03.010Antoni J., Randall R. B. Unsupervised noise cancellation for vibration signals. Part I — evaluation of adaptive algorithms // Mechanical Systems and Signal Processing. – 2004. – Vol. 18, Issue 1. – P. 89–101. – Available at: https://doi.org/10.1016/S0888-3270(03)00012-8Antoni, J., & Randall, R. B. (2004). Unsupervised noise cancellation for vibration signals. Part I evaluation of adaptive algorithms // Mechanical Systems and Signal Processing, 18(1), pp. 89-101. (In English). Available at: https://doi.org/10.1016/S0888-3270(03)00012-8Gear crack detection by adaptive amplitude and phase demodulation / D. Brie [et al.] // Mechanical Systems and Signal Processing. – 1997. – Vol. 11, Issue 1. – P. 327–335. – Available at: https://doi.org/10.1006/mssp.1996.0068Brie, D., Tomzak, M., Oehlmann, H., & Richard, A. (1997). Gear crack detection by adaptive amplitude and phase demodulation. Mechanical Systems and Signal Processing, 11(1), pp. 327-335. (In English). Available at: https://doi.org/10.1006/mssp.1996.0068Chaturvedi G. K., Thomas D. W. Adaptive noise cancelling and conditional monitoring // Journal of Sound Vibration. – 1981. – Vol. 76, Issue 3. – Р. 391–405. – Available at: https://doi.org/10.1016/0022-460X(81)90519-8Chaturvedi, G. K., & Thomas, D. W. (1981). Adaptive noise cancelling and conditional monitoring. Journal of Sound Vibration, 76(3), pp. 391-405. (In English). Available at: https://doi.org/10.1016/0022-460X(81)90519-8Dybala J., Zimroz R. Rolling bearing diagnosing method based on Empirical Mode Decomposition of machine vibration signal // Applied Acoustic. – 2014. – Vol. 77. – P. 195–203. – Available at: https://doi.org/10.1016/j.apacoust.2013.09.001Dybala, J., & Zimroz, R. (2014). Rolling bearing diagnosing method based on Empirical Mode Decomposition of machine vibration signal. Applied Acoustic, 77, pp. 195-203. (In English). Available at: https://doi.org/10.1016/j.apacoust.2013.09.001

The authors declare that there are no conflicts of interest present.