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Fuzzy based fault detection for direct torque control of three phase induction motor drive
R.S. Kumar, S. Jayanandhini, J. Jenisha, , S. Madhumitha
Published in American Institute of Physics Inc.
Volume: 2128
Induction motors are generally employed in industries for various applications due to their enhanced performance, intrinsic ruggedness and reliability. Usually monitoring the condition of the induction motor is an arduous task. Also, it is an indispensable need for maintaining the performance of the machine. In this paper, a model for monitoring the condition of the DTC based induction motor drive is proposed using advanced soft computing technique, fuzzy logic. This paper signifies the mathematical modeling of a three phase induction motor drive fed by three phase voltage source inverter using direct torque control strategy. It is necessary that these machines work efficiently with superior quality all the time. Also, If any fault occurs in machine it is essential to identify and diagnose the particular fault within the minimum possible time. Using MATLAB/SIMULINK software, here direct torque control of induction motor is implemented and the various fault issues of induction motor is presented with the help of fuzzy based fault detection system. An intelligent modeling technique is adopted as an identifier for different types of faults. The three phase stator currents are estimated and applied as an input to the fuzzy detector system. In this model, time acts as an important parameter in fault detection and in decision making. It plays a vital role for taking suitable corrective action according to the nature of the fault that occurs in the machine. © 2019 Author(s).
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JournalData powered by TypesetAIP Conference Proceedings
PublisherData powered by TypesetAmerican Institute of Physics Inc.