scholarly journals Feature Knowledge Based Fault Detection of Induction Motors Through the Analysis of Stator Current Data

2016 ◽  
Vol 65 (3) ◽  
pp. 549-558 ◽  
Author(s):  
Ting Yang ◽  
Haibo Pen ◽  
Zhaoxia Wang ◽  
Che Sau Chang
Keyword(s):  
Fault Detection ◽  
Induction Motors ◽  
Current Data ◽  
Stator Current ◽  
Knowledge Based

Combined Vibration and Stator Current Techniques for Induction Motors Fault Detection – A Review

2021 ◽  
Author(s):  
Julio Ayala ◽  
Matias Meira ◽  
Carlos Verucchi ◽  
Guillermo Bossio ◽  
Gerardo Acosta
Keyword(s):  
Fault Detection ◽  
Induction Motors ◽  
Stator Current

A Kalman Filter Based Technique for Stator Turn-Fault Detection of the Induction Motors

2017 ◽  
Vol 18 (6) ◽  
Author(s):  
Teymoor Ghanbari ◽  
Haidar Samet
Keyword(s):  
Kalman Filter ◽  
Fault Detection ◽  
High Performance ◽  
Induction Motors ◽  
Simple Technique ◽  
Harmonic Distortion ◽  
Stator Current ◽  
Three Phase ◽  
Power Frequency ◽  
Faults Diagnosis

AbstractMonitoring of the Induction Motors (IMs) through stator current for different faults diagnosis has considerable economic and technical advantages in comparison with the other techniques in this content. Among different faults of an IM, stator and bearing faults are more probable types, which can be detected by analyzing signatures of the stator currents. One of the most reliable indicators for fault detection of IMs is lower sidebands of power frequency in the stator currents. This paper deals with a novel simple technique for detecting stator turn-fault of the IMs. Frequencies of the lower sidebands are determined using the motor specifications and their amplitudes are estimated by a Kalman Filter (KF). Instantaneous Total Harmonic Distortion (ITHD) of these harmonics is calculated. Since variation of the ITHD for the three-phase currents is considerable in case of stator turn-fault, the fault can be detected using this criterion, confidently. Different simulation results verify high performance of the proposed method. The performance of the method is also confirmed using some experiments.

Fault Detection of Induction Motors Using Just In Time Classifiers

2021 ◽  
Author(s):  
Saaeede Hazbavi ◽  
Roozbeh Razavi-Far ◽  
Mohammad Mehdi Arefi ◽  
Alireza Khayatian ◽  
Mehrdad Saif
Keyword(s):  
Fault Detection ◽  
Induction Motors ◽  
Just In Time
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