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Fault Diagnosis of Three Phase Induction Motor Using Current Signal, MSAF-Ratio15 and Selected Classifiers

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
A degradation of metallurgical equipment is normal process depended on time. Some factors such as: operation process, friction, high temperature can accelerate the degradation process of metallurgical equipment. In this paper the authors analyzed three phase induction motors. These motors are common used in the metallurgy industry, for example in conveyor belt. The diagnostics of such motors is essential. An early detection of faults prevents financial loss and downtimes. The authors proposed a technique of fault diagnosis based on recognition of currents. The authors analyzed 4 states of three phase induction motor: healthy three phase induction motor, three phase induction motor with 1 faulty rotor bar, three phase induction motor with 2 faulty rotor bars, three phase induction motor with faulty ring of squirrel-cage. An analysis was carried out for original method of feature extraction called MSAF-RATIO15 (Method of Selection of Amplitudes of Frequencies – Ratio 15% of maximum of amplitude). A classification of feature vectors was performed by Bayes classifier, Linear Discriminant Analysis (LDA) and Nearest Neighbour classifier. The proposed technique of fault diagnosis can be used for protection of three phase induction motors and other rotating electrical machines. In the near future the authors will analyze other motors and faults. There is also idea to use thermal, acoustic, electrical, vibration signal together.
Twórcy
autor
  • AGH University of Science and Technology, Faculty of Electrical Engineering, Automatics, Computer Science and Biomedical Engineering, Department of Automatics and Biomedical Engineering, Al. A. Mickiewicza 30, 30-059 Kraków, Poland
autor
  • AGH University of Science and Technology, Faculty of Electrical Engineering, Automatics, Computer Science and Biomedical Engineering, Department of Automatics and Biomedical Engineering, Al. A. Mickiewicza 30, 30-059 Kraków, Poland
autor
  • AGH University of Science and Technology, Faculty of Electrical Engineering, Automatics, Computer Science and Biomedical Engineering, Department of Power Electronics and Energy Control Systems, Al. A. Mickiewicza 30, 30-059 Kraków, Poland
autor
  • AGH University of Science and Technology, Faculty of Electrical Engineering, Automatics, Computer Science and Biomedical Engineering, Department of Power Electronics and Energy Control Systems, Al. A. Mickiewicza 30, 30-059 Kraków, Poland
autor
  • University of Zilina, faculty of Electrical Engineering, 1 Univerzitna Str., 01026 Zilina, Slovakia
autor
  • University of Zilina, faculty of Electrical Engineering, 1 Univerzitna Str., 01026 Zilina, Slovakia
autor
  • Shaqra University, College of Computing and Information Technology, Department of Computer Science, Kingdom of Saudi Arabia
autor
  • Najran University, Electrical Engineering Department, Kingdom of Saudi Arabia
autor
  • National Research Council of Italy, CNR IMAMOTER, Institute for Agricultural and Earthmoving Machinery, Italy
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Uwagi
EN
This work has been partly supported by AGH University of Science and Technology, grant no. 11.11.120.612, grant no. 11.11.120.815, grant no. 11.11.120.354. This work has been partly supported by the Grant Agency VEGA from the Ministry of Education of Slovak Republic under contract 1/0602/17.
PL
Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2018).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-040c5c21-9946-4b90-a0ef-854bcb4c3f50
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