2020, 4 (37)

Operation of nuclear industry facilities

Article NameThe Identification of Pre-Failure Conditions of Oil Coolers of NPP MCP by Operating Parameters
AuthorsV.V. Krivin1, V.Ya. Shpicer2, V.A. Tolstov3, I.O. Ishigov4
Address

 

Volgodonsk Engineering Technical Institute the branch of National Research Nuclear University “MEPhI”,

Lenina street, 73/94, Volgodonsk, Russia 347360

1ORCID iD: 0000-0003-0903-0786

WoS Researcher ID: E-2267-2018

e-mail: vvkrivin@mephi.ru

2ORCID iD: 0000-0002-5051-5091

e-mail: shpitser@mephi.ru

3ORCID iD: 0000-0001-7144-5195

WoS ResearcherID: F-1032-2017

e-mail: v-tolstov-2017@mail.ru

4ORCID iD: 0000-0002-5829-6989

WoS Researcher ID: E-2448-2018

e-mail: ioishigov@mephi.ru

 

AbstractThe article deals with the results of empirical modeling of the oil system of the main circulation pumps of a nuclear power plant, designed for oil supply to support bearings and their cooling. The empirical model extends the industrial monitoring platform with a sliding linear predictor to maintain the operational safety and operability of the MCP. The initial data for the predictor are the controlled parameters of the MCP
Keywordsmonitoring, forecasting, NPP safety, main circulation pump, heat exchanger, digital signal processing, nonparametric statistics, regulatory limits, Sokolov-Singer indicator, indicator of thermal efficiency
LanguageRussian
References
  1. Slavutskiy L.A. Osnovy` registracii danny`x i planirovaniya e`ksperimenta [The Basis of Data Registration and Experiment Planning]. Cheboksary: Izdatel'stvo CHGU [Cheboksary: Publishing house of ChGU]. 2006. 200 p. (in Russian).
  2. Fomin Ya.A. Teoriya vy`brosov sluchajny`x processov [The Theory of Random Process Outliers]. Moskva: Svyaz`. [Moscow: Communication]. 1980. 216 p. (in Russian).
  3. Coelho L.P., Richart V. Postroenie sistem mashinnogo obucheniya na yazy`ke Python [The Building of Machine Learning Systems in Python Language]. Moskva: DMK Press [Moscow: DMK Press]. 2016. 302 p. (in Russian).
  4. Flach P. Mashinnoe obuchenie. Nauka i iskusstvo postroeniya algoritmov, kotory`e izvlekayut znaniya iz danny`x [The Machine Learning. The Science and Art of Building Algorithms that Extract Knowledge from Data]. Moskva: DMK Press [Moscow: DMK Press]. 2015. 400 p.
    (in Russian).
  5. Loskutov A.Yu., Mikhailov A.S. Osnovy` teorii slozhny`x system [The Basis of Comples System Theory]. Moscow-Izhevsk: Institut komp`yuterny`x issledovanij [The Institute of Computer Sciense]. 2007. 620 p. (in Russian).
  6. Sysoev Yu.S. Ispol`zovanie vremenny`x ryadov dlya formirovaniya promezhutkov odnotipnogo povedeniya parametrov ob``ekta pri razlichny`x sposobax prognozirovaniya [The Time Series Usage for the Formation of Intervals of Same Type Behavior of Object Parameters with Different Forecasting Methods]. Izmeritel`naya texnika [Measuring equipment]. 2018. №2. P. 8-12
    (in Russian).
  7. Orlov A.I. Prikladnaya statistika [Applied Statistics]. Moskva: Ekzamen [Moscow: Examination]. 2004. 656 p. (in Russian).
  8. Orlov Yu.N., Shagov D.O. Indikativny`e statistiki dlya nestacionarny`x vremenny`x ryadov [Indicative Statistics for Non-Stationary Time Series]. Preprinty IPM im. M.V. Keldysha [Keldysh Institute Preprints. M.V. Keldysh]. 2011. N53. 20 p. URL:  http://library.keldysh.ru/
    preprint.asp?id=2011-53 (in Russian).
  9. Zinger N.M. Gidravlicheskie i teplovy`e rezhimy` teplofikacionny`x sistem [Hydraulic and Thermal Modes of Heating Systems]. Moskva: Energoatomizdat [Moscow: Energoatomizdat]. 1986. 320 p. (in Russian).
  10. Sokolov E.Ya. Teplofikaciya i teplovy`e seti [Heating and Heat Networks]. Moskva: Izdatel'stvo MEI [Moscow: MPEI Publishing House]. 1999. 472 p. (in Russian).
  11. Uong X. Osnovny`e formuly` i danny`e po teploobmenu dlya inzhenerov [Basic Formulas and Data of Heat Transfer for Engineers]. Moskva: Atomizdat [Moscow: Atomizdat]. 1979. 216 p.
    (in Russian).
  12. Belkin A.P., Stepanov O.A. Diagnostika teploe`nergeticheskogo oborudovaniya [Diagnostics of Heat and Power Equipment]. Sankt-Peterburg: Lan`[St. Petersburg: Lan]. 2018. 240 p. URL: https://e.lanbook.com/book/105988 (in Russian).
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