- Tytuł:
- Time - frequency method and artificial neural network classifier for induction motor drive system defects classification
- Autorzy:
-
Behim, Meriem
Merabet, Leila
Saad, Salah - Powiązania:
- https://bibliotekanauki.pl/articles/31341644.pdf
- Data publikacji:
- 2024
- Wydawca:
- Polska Akademia Nauk. Polskie Towarzystwo Diagnostyki Technicznej PAN
- Tematy:
-
energy
L-kurtosis
wavelet packet decomposition
multilayer perceptron neural network
induction motor defects
vibratory signals - Opis:
- In this paper, by introducing two statistical parameters, energy and L-kurtosis, a new fault diagnostic system combining Wavelet Packet Decomposition and Multilayer Perceptron Neural Network is designed to improve efficiency and precision of induction motor defects diagnosis. This method is applied to vibratory signals of asynchronous motor running at two different rotational speeds (1500 rpm and 2000 rpm) at a sampling frequency of 8 KHz to detect three main types of defects: bearing faults, load imbalance and misalignment. These speeds are considered as the usual medium running speeds of induction motor. According to the results, the high performance and accuracy of this new faults diagnostic system is proved and confirmed, thus it can be used in the detection of other machines defects.
- Źródło:
-
Diagnostyka; 2024, 25, 1; art. no. 2024110
1641-6414
2449-5220 - Pojawia się w:
- Diagnostyka
- Dostawca treści:
- Biblioteka Nauki
Artykuł