Faults Feature Extraction Using Discrete Wavelet Transform and Artificial Neural Network for Induction Motor Availability Monitoring—Internet of Things Enabled Environment

Faults Feature Extraction Using Discrete Wavelet Transform and Artificial Neural Network for Induction Motor Availability Monitoring—Internet of Things Enabled Environment

<b>Motivation:</b> This paper presents the high contact resistance (HCR) and rotor bar faults by an extraction method for an induction motor using Discrete Wavelet Transform (DWT) and Artificial Neural Network (ANN). The root mean square (RMS) and mean features are obtained using DWT, an...

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Bibliographic Details
Main Authors: Muhammad Zuhaib, Faraz Ahmed Shaikh, Wajiha Tanweer, Abdullah M. Alnajim, Saleh Alyahya, Sheroz Khan, Muhammad Usman, Muhammad Islam, Mohammad Kamrul Hasan
Format: Article
Language:English
Published: MDPI AG 2022-10-01
Series:Energies
Subjects:
induction motors
MCSA
DWT
ANN
IoT security
resources availability
Online Access:https://www.mdpi.com/1996-1073/15/21/7888

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