A systematic literature review of the predictive maintenance from transportation systems aspect

OÖ Ersöz, AF İnal, A Aktepe, AK Türker, S Ersöz - Sustainability, 2022 - mdpi.com
With the rapid progress of network technologies and sensors, monitoring the sensor data
such as pressure, temperature, current, vibration and other electrical, mechanical and …

A new acoustic emission-based approach for supply disturbances evaluation in three-phase induction motors

GB Lucas, BA De Castro, MA Rocha… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
The interruption of a three-phase induction motor (TIM) on production lines represents a
high financial and operational cost. However, these machines are often exposed to …

Application of Tiny Machine Learning in Predicative Maintenance in Industries

SO Ooko, SM Karume - Journal of Computing Theories and …, 2024 - dl.futuretechsci.org
The continued advancements in Internet of Things (IoT) and Machine Learning (ML)
technologies have led to their adoption in various domains including in industries for …

Universal cyber physical system, a prototype for predictive maintenance

KK Kee, SLB Yew, YS Lim, YP Ting… - Bulletin of Electrical …, 2022 - beei.org
Abstract Industrial 4.0 technology of cyber-physical system enables real-time monitoring,
sensing and actuating of physical machinery for predictive maintenance that replaces the …

Providing fault detection from sensor data in complex machines that build the smart city

A Gascón, R Casas, D Buldain, Á Marco - Sensors, 2022 - mdpi.com
Household appliances, climate control machines, vehicles, elevators, cash counting
machines, etc., are complex machines with key contributions to the smart city. Those devices …

Failure Prediction for High Voltage Induction Motor using Artificial Neural Network (ANN)

AMB Zainol, NRAB Burhani - 2023 International Conference On …, 2023 - ieeexplore.ieee.org
This study assesses the machine learning model used to analyze the most influential factor
(MIF) of maintenance in rotating motor or induction motor and correlate the factors. There are …

Multilabel external fault classification of induction motor using machine learning models

LR Chandran, K Ilango, MG Nair… - 2022 Third …, 2022 - ieeexplore.ieee.org
The industrial sector relies heavily on induction motors. Because of the age of the machine
in service, fault diagnosis and condition assessment (FDCA) of rotating machines becomes …

Detecting most influential parameters in high voltage induction motor failure using logistic regression analysis

AMB Zainol, NRAB Burhani - 2022 2nd International Seminar …, 2022 - ieeexplore.ieee.org
This study identifies the most influential factors of rotating machines or induction motors that
are commonly used in the industry such as oil and gas industry. The data gathered in the …

Prediction of Induction Motor Faults Using Machine Learning

A Abdulkareem, T Anyim, O Popoola, J Abubakar… - Heliyon, 2024 - cell.com
Unplanned downtime in industrial sectors presents significant challenges, impacting both
production efficiency and profitability. To tackle this issue, companies are actively working …

Early fault detection for rotating machinery onboard ships motor using fuzzy logic and k-means

V Pandya, S Agrawal, S Jain, B Jayaswal - International Conference on …, 2022 - Springer
Many industries have now adopted the predictive maintenance approach to increase the life
span of the equipment. So as a part of predictive maintenance, early estimation of faults in …