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Fault diagnosis of electrical faults of three-phasei nduction motors using acoustic analysis

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Fault diagnosis techniques of electrical motors can prevent unplanned downtime and loss of money, production, and health. Various parts of the induction motor can be diagnosed: rotor, stator, rolling bearings, fan, insulation damage, and shaft. Acoustic analysis is non-invasive. Acoustic sensors are low-cost. Changes in the acoustic signal are often observed for faults in induction motors. In this paper, the authors present a fault diagnosis technique for three-phase induction motors (TPIM) using acoustic analysis. The authors analyzed acoustic signals for three conditions of the TPIM: healthy TPIM, TPIM with two broken bars, and TPIM with a faulty ring of the squirrel cage. Acoustic analysis was performed using fast Fourier transform (FFT), a new feature extraction method called MoD-7 (maxima of differences between the conditions), and deep neural networks: GoogLeNet, and ResNet-50. The results of the analysis of acoustic signals were equal to 100% for the three analyzed conditions. The proposed technique is excellent for acoustic signals. The described technique can be used for electric motor fault diagnosis applications.
Rocznik
Strony
art. no. e148440
Opis fizyczny
Bibliogr. 33 poz., rys., tab.
Twórcy
autor
  • Cracow University of Technology, Faculty of Electrical and Computer Engineering, Department of Electrical Engineering, ul. Warszawska 24,31-155 Kraków, Poland
  • Cracow University of Technology, Faculty of Electrical and Computer Engineering, Department of Electrical Engineering, ul. Warszawska 24,31-155 Kraków, Poland
  • AGH University of Krakow, Faculty of Electrical Engineering, Automatics, Computer Science and Biomedical Engineering, Department of PowerElectronics and Energy Control Systems, al. A. Mickiewicza 30, 30-059 Kraków, Poland
  • AGH University of Krakow, Faculty of Electrical Engineering, Automatics, Computer Science and Biomedical Engineering, Department of PowerElectronics and Energy Control Systems, al. A. Mickiewicza 30, 30-059 Kraków, Poland
  • AGH University of Krakow, Faculty of Electrical Engineering, Automatics, Computer Science and Biomedical Engineering, Department of AutomaticControl and Robotics, al. A. Mickiewicza 30, 30-059 Krakw, Poland
autor
  • Faculty of Mechanical Engineering, Opole University of Technology, Opole 45-758, Poland University of Religions and Denomina, Qom, Iran
  • University of Zilina, Faculty of Mechanical Engineering, Department of Design and Machine Elements, Univerzitna 1, 010 26 Zilina, Slovakia
  • University of Zilina, Faculty of Electrical Engineering and Information Technology, 8215/1 Univerzitna, 01026 Zilina, Slovakia
  • University of Zilina, Faculty of Electrical Engineering and Information Technology, 8215/1 Univerzitna, 01026 Zilina, Slovakia
autor
  • Wenzhou University, College of Mechanical and Electrical Engineering, Wenzhou, 325 035, China
  • Sao Paulo State University, Department of Electrical Engineering, Av. Eng. Luís Edmundo Carrijo Coube, 14-01, Bauru, Sao Paulo, Brazil
  • Najran University Saudi Arabia, Electrical Engineering Department, College of Engineering, Najran 61441, Saudi Arabia
  • Faculty of Mechanical Engineering, Opole University of Technology, Opole 45-758, Poland
  • Faculty of Integrated Technologies, Universiti Brunei Darusalam, Jalan Tungku Link, Gadong BE1410, Brunei
autor
  • China Jiliang University, College of Quality and Safety Engineering, Hangzhou 310018, China
Bibliografia
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Uwagi
Opracowanie rekordu ze środków MNiSW, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2024).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-62d04aaa-be75-438f-9128-62e40fd9c612
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