الفهرس 
IntroductionOnly 14 pages are availabe for public view
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Abstract
Condition monitoring of induction motors can significantly reduce the cost of maintenance and the risk of unexpected failures by allowing the early detection of potentially faults. It also improves service to customers by using the predictive maintenance. There are many methods of condition monitoring including thermal monitoring, noise monitoring, vibration monitoring, motor current signature analysis, partial discharge, expert systems, fuzzy logic system and artificial neural network. from this point, it is important tonote the condition monitoring of induction machines. A model for the induction motor was developed in this thesis to be used in MATLAB. Also, a thermal model for the induction motor was developed in order to obtain an accurate estimation of the temperature. This can be done using the current as a factor proportional to temperature. Using MATLAB simulation enables us to estimate the temperature at both the stator and rotor. However, the effect of the environmental conditions was not taken into account in this simulation. To achieve the best and longest motor performance, it is important to recognize the stress imposed by starting and to limit the number of starts. Therefore, it is better that the number of starts per hour of the motor no more than 6 times. The stator temperature of induction motor is displayed by using Arduino until monitoring to the fault in induction motor before it happens. An experimental test the induction motor enables us to measure the temperature at the stator windings using a thermocouple. This motor was coupled with a generator to act as a load. The effect of temperature rise on the performance of the induction motor was studied at no load, ¼, ½, ¾, and full load. However, in contrast to the simulation procedure, a sensor cannot be used to measure the temperature at the rotor, and the experimental results were in a good agreement with simulated results.