THE online condition monitoring of induction motors is
becoming increasingly important. The relevance of this
subject arises from the fact that induction motors are key
elements in most industrial processes and in some tasks of
the daily life [1]. The stator winding insulation is normally
the most weakness component during thermal overload,
since its thermal limit is reached before that of any other
motor component. About 35-40% of induction motor
failures are related to stator winding insulation failure [2- 4].
It is commonly assumed that the motor's life is reduced by
50% for every 10 oC increase above its stator winding
temperature limit.
The accurate monitoring of the stator winding temperature is
critical to proactively protect the motor, hence estimating the
stator winding temperature (Ts) has great importance [5, 6,
7]. Aside from the direct stator winding temperature
measurement, the thermal model-based and the motor
parameter-based temperature estimation methods are two
major techniques for thermal protection. The modified
model provides an accurate temperature sensor used to
measure average winding temperature for validation
purpose. This sensor isn't available in Matlap Simulink.
Temperature estimation methods based on thermal and
electrical motor models are found in literature [5], [6].
Nevertheless, these methods fail when the model changes,
for instance, owing to cooling system failures or its
dependence on operating conditions (e.g., motor fan speed).
Aside from the aforementioned techniques, the stator