Electric fault diagnosis and detection in an induction machine using RMS based method
Yükleniyor...
Tarih
2022
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Institute of Electrical and Electronics Engineers Inc.
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
Nowadays, induction machines are widely used in industry thankful to their advantages comparing to other technologies. Indeed, there is a big demand because of their reliability, robustness and cost. The objective of this paper is to deal with diagnosis, detection and isolation of faults in a three-phase induction machine. Among the faults, Inter-turn short-circuit fault (ITSC), current sensors fault and single-phase open circuit fault are selected to deal with. However, a new method is developed for fault detection using residual errors generated by the root mean square (RMS) of phase currents. This approach is based on an asymmetric nonlinear model of Induction Machine where the winding fault of the three axes frame state space is taken into account. In addition, current sensor redundancy and sensor fault detection and isolation (FDI) are adopted to ensure safety operation of induction machine drive. Finally, a validation is carried out by simulation in healthy and faulty operation modes to show the benefit of the proposed method to detect and to locate with, a high reliability, the three types of faults. © 2022 IEEE.
Açıklama
2022 International Conference on Control, Automation and Diagnosis, ICCAD 2022 -- 13 July 2022 through 15 July 2022 -- -- 182187
Anahtar Kelimeler
Asymmetric Nonlinear Model, Current sensor fault, Fault detection, Fault diagnosis, Induction machine, Inter-Turn Short-Circuit Fault, Isolation, Root mean square
Kaynak
2022 International Conference on Control, Automation and Diagnosis, ICCAD 2022
WoS Q Değeri
Scopus Q Değeri
N/A
Cilt
Sayı
Künye
Akrad, A., Sehab, R. ve Alyoussef, F. (2022). Electric fault diagnosis and detection in an induction machine using RMS based method. 2022 International Conference on Control, Automation and Diagnosis, ICCAD 2022.
