Electro-mechanical Parameter Determination of Induction Motor Using Generalized Regression Neural Network

Abstract

Overheating of electrical components in household appliances might occur sometimes due to short circuit faults. Degradation of electrical equipment may take place due to voltage fluctuations. Hence, an electrical protection system is required for electrical equipment.  A detection system can  monitor and capable of providing specific protection. This project is aimed to develop  a fault detection and clearance system  which will monitor , detect  and  protect  equipment  from  electrical  faults. A protective system has been designed using Arduino,  that  acts  as  a  microcontroller with  the  help of   current  sensor, voltage sensor , IR and  temperature  sensor  embedded  into  it. If current, voltage, speed  and  temperature values exceeded the preset values, the  device  begins  to  realize  that  some  abnormal  conditions  or  faults  took  place  in  the equipment.  With the  help  of  relay and  Arduino,  equipment was protected from fault. The generalized regression Neural network (GRNN) model was trained using the measured data. The proposed GRNN model had been tested with new data sets using MATLAB-SIMULINK. The test result reveals that GRNN model can effectively determine the electro-mechanical parameters of induction motor.