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Signature Analysis as a Medium for Detecting Faults in Induction Motor
Date
2018-03-11Author
Noor Al-Deen , K.
Hummes, Detlef
Type
Conference Paper
Metadata
Show full item recordAbstract
An induction motor (IM) is an essential component
in many industries and power plants. Therefore, for most
applications requiring IMs, the reliability, efficiency and
performance are of great importance. Also, since the costs of break
down and unforeseen shut downs are extremely high and the need
for high reliability is extensive, condition monitoring of IM became
increasing significantly. There are several condition monitoring
techniques, e.q. vibration and thermal monitoring. However, those
monitoring techniques require sensors, which might be expensive.
On the other hand, electrical monitoring such as Motor Current
Signature Analysis (MCSA) does not require the use of extra
sensors. The MCSA technique makes use of the stator current
spectrum for detecting fault frequencies. When there is a fault in
the motor, the frequency of the line current becomes different than
that of a healthy motor. So, in this work, unbalance and
misalignment fault detection using MCSA in LabVIEW with the
help of FFT and ANN will be presented