Open AccessNeural Network Based Monitoring, Protection & Fault Detection of Induction Motor Using PLC
Author(s) -
Devendra Somwanshi,
Arvind Kumar
Publication year - 2018
Publication title -
international journal of engineering and technology
Language(s) - English
Resource type - Journals
ISSN - 2227-524X
DOI - 10.14419/ijet.v7i2.24.12019
Subject(s) - induction motor , artificial neural network , motor soft starter , control theory (sociology) , control engineering , torque , matlab , engineering , computer science , fault (geology) , control (management) , voltage , artificial intelligence , electrical engineering , physics , seismology , geology , thermodynamics , operating system
Induction motors used mostly in industrial, commercial applications & are seldom denominated power horse of industry. To reduce the motor starting current soft starter requirement is increasing day by day & to maintain the torque proportionally with the load requirement. Now intelligent soft starters evolved to improve the motor starting. This work is comprised of development of an Artificial Neural Network control regime for closed loop of induction motor. The same has been achieved using a standard 0.75 KW three phase induction motor using Matlab, PLC, SCADA & DRIVE. The Artificial Neural Network scheme is compared with traditional Proportional control regime. We have observed that the performance of ANN Induction Motor control Algorithm has been 14-21 % better than only Proportional Motor Control algorithm.