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Scientific Article O'zbekcha Open Access

Sun’iy neyron tarmog‘i yordamida asinxron motorlarning nosozliklarni monitoring qilish va diagnostika qilish

NIZAMOV J.A.

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Journal
Fan va texnologiyalar taraqqiyoti
Issue
2-son
Pages
168–173
Published
25.04.2026
Views
2 7

Abstracts

Three-phase induction motors play a critical role in industrial applications, and their failures may lead to serious operational problems. This study focuses on early fault detection using current, temperature, and vibration signals combined with artificial intelligence techniques. Experiments were performed on a test bench simulating stator unbalance, bearing damage, and shaft misalignment. A NARX neural network was developed and optimized for fault classification. The results demonstrate high performance, achieving accuracies of 94.2% for faulty motor, 95% for misalignment, 98% for bearing faults, and 95% for stator faults
Keywords: artificial intelligence; neural networks; induction motor; fault monitoring; fault diagnosis; classification; NARX. Uch fazali asinxron motorlar (UFA) zamonaviy sanoatning deyarli barcha tarmoqlarida keng qo‘llaniladigan asosiy elektr yuritma elementlaridan hisoblanadi. Ular oziq-ovqat sanoatidagi sanitariya talablari yuqori bo‘lgan muhitlardan tortibneft-kimyometallurgiya va og‘ir sanoat kabi murakkab ekspluatatsiya sharoitlarigacha bo‘lgan jarayonlarda samarali ishlatiladi. Past tannarxk

Article Content

kirish signali, oldingi chiqish (javob) signali, y(k)y(k)y(k) esa baholangan (hisoblangan) chiqishni anglatadi. Tarmoqdagi moviy bloklar kechikish elementlarini, raqamlar bilan belgilangan doiralar esa yashirin qatlamdagi neyronlarni ifodalaydi. Mazkur eksperimental stend real sanoat sharoitida ishlayotgan dvigatelning ish rejimini modellashtirish imkonini beradi. Tadqiqot jarayonida ikki asosiy turdagi nosozliklar tahlil qilindi. Birinchi toifa mexanik nosozliklar bo‘lib, ularga milning muvozanatsizligi va rulmanlarning shikastlanishi kiradi. Ushbu nosozliklarni aniqlashda asosan vibratsiya va harorat signallaridan foydalanildi. Ikkinchi toifa elektr nosozliklar bo‘lib, ular stator “Fan va texnologiyalar taraqqiyoti” Ilmiy-texnikaviy jurnal №2/2026 167 Mechanical engineering and energy chulg‘amlaridagi nuqsonlar bilan bog‘liq bo‘lib, bunday holatlarda o‘ram toklarining va harorat parametrlarining o‘zgarishi tahlil qilindi. 2-rasm. NARX neyron tarmog‘ining topologiyasi 3-rasmda ROC egri chizig‘i (yashil, to‘q sariq va ko‘k ranglarda) namunalar ko‘rsatilgan. Sezgirlik (sensitivity) va xoslik (specificity) qiymatlari 100% ga qanchalik yaqin bo‘lsa, sinovning aniqligi shunchalik yuqori bo‘ladi. ROC egri chizig‘i kesish (cutoff) qiymatlari o‘zgartirilganda sezgirlik va xoslik qanday o‘zgarishini namoyish etadi [3]. Ushbu tadqiqotda uch fazali asinxron motorlar uchun mo‘ljallangan monitoring va nosozliklarni diagnostika qilish tizimini yaratishda maxsus ishlab chiqilgan metodologiyadan foydalanildi. Eksperimental tadqiqotlar Braziliyada joylashgan Rio Grande do Norte Federal University (UFRN) ning mashinalar laboratoriyasida tashkil etilgan sinov stendida olib borildi. Tok, vibratsiya va harorat signallaridan tashkil topgan ma’lumotlar to‘plami NARX tipidagi neyron tarmoq uchun kirish ma’lumotlari sifatida foydalaniladigan datasetni shakllantirishda qo‘llanildi. Sinovlar motorning normal ish holatida, shuningdek, stator kuchlanishining nomutanosibligi, milning eksantrikligi va rulman nuqsonlari kabi sun’iy ravishda hosil qilingan nosozlik sharoitlarida amalga oshirildi. Keyingi bosqichlarda signallarni yig‘ish jarayoni, foydalanilgan o‘lchov qurilmalari va qo‘llanilgan usullar, shuningdek nosozlik holatlarini emulyatsiya qilish mexanizmlari batafsil bayon qilindi. Taklif etilgan metodologiyani amaliyotga tatbiq etish uchun ishlab chiqilgan blok-sxema besh asosiy moduldan iborat bo‘lib, ular test stendi, ma’lumotlarni yig‘ish tizimi, signallarni qayta ishlash bosqichi, NARX neyron tarmog‘i asosida klassifikatsiya qilish hamda yakuniy natijalarni vizual va tahliliy shaklda taqdim etish jarayonlarini o‘z ichiga oladi. Ketma-ket bosqichlar asosida motorlarning nosozlik holatlari aniqlanib, ularning ishonchli diagnostikasi amalga oshirildi [5]. Tajriba ishlarini amalga oshirishda DLB MAQ-RN rusumli eksperimental stenddan foydalanildi. Ushbu stend Andijon davlat texnika instituti Elektr muhandisligi kafedrasi laboratoriyasida o‘rnatilgan bo‘lib, uch fazali asinxron motorlarda signallarni yuqori aniqlikda yig‘ish va nosozliklarni aniqlash uchun zarur bo‘lgan texnik imkoniyatlar bilan ta’minlangan. Mazkur stend yordamida bajarilgan tajribalar natijalari ishonchli va takrorlanadigan bo‘lishi ta’minlandi. Dasturlashtirilgan nosozlik sinovlari elektr dvigatelidagi nosozliklarni signal tahlili asosida aniqlashga qaratilgan bo‘lib, maxsus ishlab chiqilgan besh xil ssenariy asosida o‘tkazildi. 3-rasm. ROC egri chizig‘i Development of science and technology Scientific and technical journal №2/2026 168 Mashinasozlik va energetika 4-rasm. Jarayonning blok-sxemasi. Ushbu ssenariylar dvigatelning turli ekspluatatsion holatlarini aks ettirish maqsadida ishlab chiqilgan. Ular normal ish rejimidan tashqari, milning nomutanosibligi, podshipniklarning shikastlanishi hamda stator toki nomutanosibligi kabi sun’iy ravishda yaratilgan nosozlik holatlarini ham o‘z ichiga oladi. Sinovlar dvigatelning uch xil aylanish tezligida amalga oshirildi: 900 ayl/min, 1200 ayl/min va 1800 ayl/min. Mazkur ish doirasida esa faqat 1800 ayl/min tezlikda olingan eksperimental ma’lumotlar tahlil qilinadi. Ushbu holat mos yozuv (referens) rejimi sifatida qabul qilinib, ideal sharoitlarda dvigatelning normal ishlash holatini ifodalaydi. Tajriba davomida tebranish (vibratsiya), fazalardagi elektr toki va harorat signallari uzluksiz ravishda yig‘ib olindi. 20-rasmda datchiklar o‘rnatilgan dvigatelning umumiy ko‘rinishi tasvirlangan. Mos ravishda, 1 va 2-rasmlarda vibratsiya va tok signallarining vaqt sohasidagi grafiklari, 3 va 4-rasmlarda esa ushbu signallarning chastota sohasidagi spektral ko‘rinishlari keltirilgan. Bundan tashqari, ideal ish sharoitidagi dvigatel haroratining o‘zgarishi ham alohida ko‘rinishda taqdim etilgan [6]. 5-rasm. Tebranish signalining vaqt sohasidagi ko‘rinish “Fan va texnologiyalar taraqqiyoti” Ilmiy-texnikaviy jurnal №2/2026 169 Mechanical engineering and energy 6-rasm. Tebranish signalining chastota sohasidagi ko‘rinishi Xulosa. Ushbu tadqiqot doirasida uch fazali asinxron motorlarda nosozliklarni erta aniqlash va ularning holatini baholashga qaratilgan, aqlli yondashuvga asoslangan integratsiyalashgan diagnostika usuli taklif etildi. Tok, vibratsiya va harorat signallaridan olinadigan ma’lumotlar asosida NARX turidagi sun’iy neyron tarmog‘i ishlab chiqildi hamda uning ishlash ko‘rsatkichlari optimallashtirildi. O‘tkazilgan tadqiqotlar natijalari taklif etilgan yondashuv yuqori aniqlikni ta’minlashini ko‘rsatdi: nosoz motor holatini aniqlash aniqligi 94,2%, milning nomutanosibligini aniqlash 95%, rulman nosozliklarini aniqlash 98% hamda stator nosozliklarini aniqlash 95% ni tashkil etdi. Eksperimental test stendida bajarilgan sinovlar shuni tasdiqladiki, signallarni vaqt va chastota domenlarida kompleks tahlil qilish hamda sun’iy neyron tarmoqlarga asoslangan klassifikatsiya algoritmlarini birgalikda qo‘llash mexanik va elektr nosozliklarni ishonchli tarzda identifikatsiya qilish imkonini beradi. Ushbu yondashuv faqat bitta diagnostik parametrga tayanuvchi an’anaviy monitoring tizimlariga nisbatan sezilarli ustunlikka ega ekanligi aniqlandi [7]. Olingan natijalar shuni ko‘rsatadiki, tok, vibratsiya va harorat signallarini birgalikda tahlil qilishga asoslangan kompleks monitoring tizimi nosozliklarni dastlabki bosqichlarda aniqlash imkonini beradi. Shuningdek, NARX turidagi neyron tarmog‘i dinamik jarayonlarni modellashtirishda samarali va ishonchli vosita ekanligi tajriba orqali tasdiqlandi. Taklif etilgan tizim sanoat sharoitida kutilmagan to‘xtashlar sonini kamaytirish, energiya samaradorligini oshirish va texnik xizmat ko‘rsatish bilan bog‘liq xarajatlarni qisqartirishga xizmat qilishi mumkin.Kelgusidagi tadqiqotlarda ishlab chiqilgan modelni boshqa turdagi nosozliklarni aniqlashga moslashtirish, uni real sanoat obyektlari sharoitida sinovdan o‘tkazish, shuningdek, onlayn monitoring va raqamli platformalar bilan integratsiya qilish istiqbolli ilmiy yo‘nalishlar sifatida ko‘rib chiqiladi

References (18)

  1. 1. J Nizamov, Sh Ergashov, DI Kurbanbaeva Phase angle measurement device between the resultable electric drive force and the electric drive force of the main harmonic magnetic field in the air gap of the industrial …AIP Conference ProceedingsAIP Conf. Proc. 3152, 040021 (2024) https://doi.org/10.1063/5.0218808
  2. 2. J Nizamov, SO Ergashov, ON Berdiyorov, UN Berdiyorov Device for measuring the resulting magnetic field of the stator winding of asynchronous motor for general industrial application AIP Conference Proceedings AIP Conf. Proc. 3152, 050013 (2024) https://doi.org/10.1063/5.0218809 June 2024
  3. 3. M Taniev, U Mirkhonov, M Rakhmatova, F Isakov, S Ergashov, J Nizamov Study of the substitution scheme of the parameters of a phase-rotor induction generator AIP Conference Proceedings Proc. 2552, 060010 (2023). https://doi.org/10.1063/5.0130746 January 2023
  4. 4. NB Pirmatov, AM Egamov, CM Giyasov, , J Nizamov NA Mamarasulov, UN Berdiyorov, Some aspects of comparing the operational properties of synchronous machines with a conventional and two mutually shifted excitation windings E3S Web of Conferences 10.1051/e3sconf/202340103056 EID: 2-s2.0-85169675134Part of ISSN: 22671242 25550403 Development of science and technology Scientific and technical journal №2/2026
  5. Mashinasozlik va energetika
  6. 5. K Alimkhodjaev, M Mirsaidov, M Khalikova, J Nizamov Transient processes of vibration machines with inertial electric drives E3S Web of Conferences 2020 | Conference paperDOI: 10.1051/e3sconf/202021601121EID: 2-s2.0-85098463210 Part of ISSN: 22671242 25550403
  7. 6. G Mustafakulova, A Egamov, U Mirkhonov, J Nizamov Calculation and study of the magnetic field of the stator winding of a turbine generatorE3S Web of Conferences 2020 | Conference paper DOI: 10.1051/e3sconf/202021601118 EID: 2-s2.0-85098455421
  8. 7. Nizamov, J., Boixanov, Z., Siddikov, I., ...Abdurahmonov, Three-phase asynchronous motor three-phase current converter for the research of electromagnetic processes AIP Conf. Proc. 3331, 030038 (2025) https://doi.org/10.1063/5.0306165
  9. 8. Nizamov, J., Bekishev, A., Mustafakulova, G., ...Khalbutayeva, Modeling of reactive power compensation of the electric arc steelmaking furnace DSP-100 UMK at JSC Uzmetkombinat AIP Conf. Proc. 3331, 010001 (2025) https://doi.org/10.1063/12.0039318
  10. 9. Boihanov Z.U. (2023). Modeling of asynchronous motor reactive power consumption on the basis of current transdusers. https://doi.org/10.5281/zenodo.10073963
  11. 10. Siddikov, I. K., Malikov, A., Makhsudov, M. T., Boikhanov, Z. U., & Uzaqov, R. (2022, June). Study of the static characteristics of the secondary stator voltage converter of the currents of an induction motor. In American Institute of Physics Conference Series (Vol. 2432, No. 1, p. 020003). https://ui.adsabs.harvard.edu/abs/2022AIPC.2432b0003S/abstract
  12. 11. Z. G. Chen, T. Lei, Z. J. Hua, B. Z. Urazali Ugli and A. R. Yigitali Ugli, "Short-term photovoltaic power generation prediction based on VMD-IGWO-LSTM," 2024 IEEE 4th International Conference on Digital Twins and Parallel Intelligence (DTPI), Wuhan, China, 2024, pp. 682-686, doi: 10.1109/DTPI61353.2024.10778814. keywords: Short-term photovoltaic power generation prediction based on VMD-IGWO-LSTM | IEEE Conference Publication | IEEE Xplore.
  13. 12. Siddikov I.X., Karimjonov D.D., Aʼzamov S.S. Uzakov R. Study on determination of an asynchronous motorʼs reactive power by the current-to-voltage converter//IOP Conference Series: Earth and Environmental Science, ICECAE-2022, doi:10.1088/17551315/1142/1/012023 Study on determination of an asynchronous motorʼs reactive power by the current-to-voltage converter — IOPscience
  14. 13. O. Ishnazarov, X. Xaydarov, “Mathematical Analysis of the Impact of External Factors on the Operating Modes of Pump Installations in the Technological Process,”, Journal of Academia Open, vol. 10, no. 1, 2025, https://doi.org/10.21070/acopen.10.2025.10507.
  15. 14. N. Pirmatov, X. Xaydarov, “Investigating the issues of energy saving by means of a mathematical model of transient processes of asynchronous engines in pump units,” (in Uzbek), Journal of Science and innovative development, vol. 6, no. 5, pp. 63-71, https://dx.doi.org/10.36522/2181-9637-2023-5-7
  16. 15. N. Pirmatov, S. Mahamadjonov, M. Matqosimov and H. Haydarov, “Characteristics of the static and dynamic operating modes of the asynchronous generator in renewable energy sources and the production of electric energy control through a frequency converter,” in 2024 II International Scientific and Practical Conference “Energy, Ecology and Technology in Agriculture”, E3S Web Conf. vol. 480, no. 01007, https://doi.org/10.1051/e3sconf/202448001007
  17. 16. N. Pirmatov, X. Xaydarov, S. Abduraxmonov and Sh. Sayitov, “Energy saving using a frequency converter in asynchronous motor operating modes,” in 2023 International Conference on Green Energy: Intelligent Transport Systems - Clean Energy Transitions (GreenEnergy 2023), E3S Web of Conf. vol. 508, no. 08011, https://doi.org/10.1051/e3sconf/202450808011
  18. 17. X. Xaydarov, K. Qarshiyev, U. Berdiyorov, “Energy saving using a frequency converter in asynchronous motor operating modes,” in 2024 AIP Conf. Proc, vol. 3152, no. 030008, https://doi.org/10.1063/5.0219049 “Fan va texnologiyalar taraqqiyoti” Ilmiy-texnikaviy jurnal №2/2026 171