Intelligent fault detection and diagnosis in three phase induction motor drive system / Shorouk Ossama Ibrahim Foad Ahmed ; Supervised Essam Elden Aboelzahab , Khaled Nagdy Salama Faris

Thesis (Ph.D.) - Cairo University - Faculty of Engineering - Department of Electrical Power and Machines

Induction motors have been intensively utilized in industrial applications, mainly due to their efficiency and reliability. It is necessary that these machines work all the time with its high performance and reliability. So it is necessary to monitor, detect and diagnosis of different faults that these motors are faced. In this work an intelligent fault detection and diagnosis for different faults of induction motor motion control system (IMMCS) is introduced. The stator currents and time are considered the inputs to the fuzzy detector and diagnose system in the proposed system. A complete motion control system has been modeled in both healthy and faulty states, the direct torque control technique (DTC) are adopted as suitable control technique especially, in traction applications, such as: Electric Vehicle and Sub-Way Metro. The proposed system is simulated by using (Matlab/Simulink) toolbox flux equations for each phase of three-phase induction motor for studying and modelling each phase separately. The proposed intelligent modelling system can be applied for any induction motor only by entering the data of the motor, such as: rated current, the proposed model introduces the Time as an important factor or variable that plays an important role either in fault detection or in corrective action according to the type of the faults. The proposed modeling system contributes foe increasing the drive system reliability and durability. The work of this thesis can be applied in the real system such as: Electric Vehicle drive system and Sub-way metro drive system

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