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Publication Type : Conference Proceedings
Publisher : Intelligent Computing, Information and Control Systems, Springer International Publishing
Source : Intelligent Computing, Information and Control Systems, Springer International Publishing, Cham (2019)
ISBN : 9783030304652
Keywords : Artificial Neural Network (ANN), Insulated gate bipolar transistors (IGBT), Overvoltage, Pulse Width Modulation (PWM)
Campus : Bengaluru
School : Department of Computer Science and Engineering, School of Engineering
Department : Computer Science, Electrical and Electronics, Electronics and Communication
Year : 2019
Abstract : In most electrical applications, the motor is fed by Pulse Width Modulated(PWM) inverters and by design they are usually in separate locations, requiring long motor leads or cables. Overvoltage is a common phenomenon in AC motor drives that are fed by long cables from PWM inverters, as they use Insulated Gate Bipolar Transistors (IGBT) with small rise time and fall time. This paper proposes an Artificial Neural Network based system to predict overvoltage at the motor terminal with long cable using the parameters cable length and motor capacity.
Cite this Research Publication : A. Joseph, Vineetha Jain, Dr. Dhanesh G. Kurup, and Mini Sujith, “A Neural Network Based Overvoltage Prediction System for Long Cable Issue”, Intelligent Computing, Information and Control Systems. Springer International Publishing, Cham, 2019.