Machine learning methods for fault diagnosis in ac microgrids: A systematic review

MM Zaben, MY Worku, MA Hassan, MA Abido - IEEE access, 2024 - ieeexplore.ieee.org
AC microgrids are becoming increasingly important for providing reliable and sustainable
power to communities. However, the evolution of distribution systems into microgrids has …

Broken bar fault detection and diagnosis techniques for induction motors and drives: State of the art

MEED Atta, DK Ibrahim, MI Gilany - IEEE Access, 2022 - ieeexplore.ieee.org
Motors are the higher energy-conversion devices that consume around 40% of the global
electrical generated energy. Induction motors are the most popular motor type due to their …

Review of machine learning based fault detection for centrifugal pump induction motors

CE Sunal, V Dyo, V Velisavljevic - IEEE access, 2022 - ieeexplore.ieee.org
Centrifugal pumps are an integral part of many industrial processes and are used
extensively in water supply, sewage, heating and cooling systems. While there are several …

[HTML][HTML] Convolutional-neural-network-based multi-signals fault diagnosis of induction motor using single and multi-channels datasets

M Abdelmaksoud, M Torki, M El-Habrouk… - Alexandria Engineering …, 2023 - Elsevier
Using deep learning in three-phase induction motor fault diagnosis has gained increasing
interest nowadays. This paper proposes a Convolutional Neural Network (CNN) model to …

Centrifugal pump fault detection with convolutional neural network transfer learning

CE Sunal, V Velisavljevic, V Dyo, B Newton, J Newton - Sensors, 2024 - mdpi.com
The centrifugal pump is the workhorse of many industrial and domestic applications, such as
water supply, wastewater treatment and heating. While modern pumps are reliable, their …

Machine learning in structural engineering

JP Amezquita-Sancheza… - Scientia …, 2020 - scientiairanica.sharif.edu
This article presents a review of selected articles about structural engineering applications of
machine learning (ML) in the past few years. It is divided into the following areas: structural …

[HTML][HTML] Faults feature extraction using discrete wavelet transform and artificial neural network for induction motor availability monitoring—internet of things enabled …

M Zuhaib, FA Shaikh, W Tanweer, AM Alnajim… - Energies, 2022 - mdpi.com
Motivation: 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 …

[HTML][HTML] A new deep learning framework for imbalance detection of a rotating shaft

M Wisal, KY Oh - Sensors, 2023 - mdpi.com
Rotor unbalance is the most common cause of vibration in industrial machines. The
unbalance can result in efficiency losses and decreased lifetime of bearings and other …

Methodology for the detection and classification of power quality disturbances using CWT and CNN

E Perez-Anaya, AY Jaen-Cuellar, DA Elvira-Ortiz… - Energies, 2024 - mdpi.com
Energy generation through renewable processes has represented a suitable option for
power supply; nevertheless, wind generators and photovoltaic systems can suddenly …

Automatic classification of rotor faults in soft-started induction motors, based on persistence spectrum and convolutional neural network applied to stray-flux signals

V Biot-Monterde, A Navarro-Navarro… - Sensors, 2022 - mdpi.com
Due to their robustness, versatility and performance, induction motors (IMs) have been
widely used in many industrial applications. Despite their characteristics, these machines …