Induction Machines Fault Detection: An Overview

2021 ◽  
Vol 24 (7) ◽  
pp. 63-71
Author(s):  
Jose de Jesus Rangel-Magdaleno
2008 ◽  
Vol 55 (12) ◽  
pp. 4200-4209 ◽  
Author(s):  
A. Bellini ◽  
A. Yazidi ◽  
F. Filippetti ◽  
C. Rossi ◽  
G.-A. Capolino

Author(s):  
Mojtaba Afshar ◽  
Salman Abdi ◽  
Ashknaz Oraee ◽  
Mohammad Ebrahimi ◽  
Richard McMahon

2019 ◽  
Vol 63 (3) ◽  
pp. 169-177
Author(s):  
Mohamed Amine Khelif ◽  
Azeddine Bendiabdellah ◽  
Bilal Djamal Eddine Cherif

Currently, with the power electronics evolution, a major research axis is oriented towards the diagnosis of converters supplying induction machines. Indeed, a converter such as the inverter is susceptible to have structural failures such as faulty leg and/or open-circuit IGBT faults. In this paper, the detection of the faulty leg and the localization of the open-circuit switch of an inverter are investigated. The fault detection technique used in this work is based essentially upon the monitoring of the root mean square (RMS) value and the calculation of the mean value of the three-phase currents. In the first part of the paper work, the faulty leg is detected by monitoring the RMS value of the three-phase currents and comparing them to the nominal value of the phase current. The second part, the open-circuit IGBT fault is localized simply by knowing the polarity of the calculated mean value current of the faulty phase. The work is first accomplished using simulation work and then the obtained simulation results are validated by experimental work conducted in our LDEE laboratory to illustrate the effectiveness, simplicity and rapidity of the proposed technique.


2017 ◽  
Vol 64 (5) ◽  
pp. 3892-3902 ◽  
Author(s):  
Yasser Gritli ◽  
Claudio Rossi ◽  
Domenico Casadei ◽  
Fiorenzo Filippetti ◽  
Gerard-Andre Capolino

Author(s):  
Damian S. Vilchis-Rodriguez ◽  
Sinisa Djurović ◽  
Alexander C. Smith

This paper investigates the sensitivity of machine electrical quantities when employed as a means of bearing fault detection in wound rotor induction generators. Bearing failure is the most common failure mode in rotating AC machinery. With the widespread use of wound rotor induction machines in modern wind power generation, achieving effective detection of bearing faults in these machines is becoming increasingly important in order to minimize wind turbine maintenance related downtime. Current signature analysis has been demonstrated to be an effective technique for achieving detection of different fault types in ac machines. However, this technique lacks sensitivity when used for detection of bearing failures and therefore sophisticated post processing techniques have recently been suggested to improve its performance. As an alternative, this paper investigates the sensitivity of a range of machine electrical quantities to bearing faults, with the aim of examining the possibility of achieving improved bearing fault detection based on identifying a clear fault spectral signature. The reported signatures can be subjected potentially to refined processing techniques to further improve fault detection.


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