Back Propagation Neural Network Algorithm based Enlistment of Induction Motor Parameters Monitoring Using Lab View

S. Vijayalakshmi, K.R. Kavitha, M. Senthilvadivu, M. Amutha and Benita C Evangelin

The Permanent Magnet Synchronous (PMS) type Induction motor is utilized in most of the mechanical applications. Induction motors use the vast majority of the electrical vitality. The principle explanation behind the utilization of the PMS motor is its dependability and straightforwardness of activity. A PMS motor's full burden proficiency is higher than different sorts of an induction motor. Also, in this way it's fundamental to screen the presentation of the PMS motor without changing its working. In this work, presents another cutting edge innovation where inserted framework is coordinated Labivew dependent on Back Propagation neural network strategy. During this procedure, various sensors have associated with the motor, and the qualities are extricated utilizing a microcontroller. It's at that point transmitting to the base station through remote correspondence, and at the base station, a Graphical User Interface with LabVIEW given which furnish the customer can interface with the system by utilizing Back Propagation Neural Network (BPNN) calculation. The proposed BPNN based induction motor control framework is approved through recreation in Matlab_2013a Simulink condition. A hardware arrangement is likewise evolved to approve the reproduction. Over 95% proficiency is accomplished at full burden condition dependent on the proposed BPNN calculation.

Volume 12 | 05-Special Issue

Pages: 439-452

DOI: 10.5373/JARDCS/V12SP5/20201779