A review of artificial intelligence methods for condition monitoring and fault diagnosis of rolling element bearings for induction motor

O AlShorman, M Irfan, N Saad, D Zhen… - Shock and …, 2020 - Wiley Online Library
The fault detection and diagnosis (FDD) along with condition monitoring (CM) and of rotating
machinery (RM) have critical importance for early diagnosis to prevent severe damage of …

Intelligent fault diagnosis of rotor-bearing system under varying working conditions with modified transfer convolutional neural network and thermal images

H Shao, M Xia, G Han, Y Zhang… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
The existing intelligent fault diagnosis methods of rotor-bearing system mainly focus on
vibration analysis under steady operation, which has low adaptability to new scenes. In this …

Advancements in condition monitoring and fault diagnosis of rotating machinery: A comprehensive review of image-based intelligent techniques for induction motors

O AlShorman, M Irfan, M Masadeh, A Alshorman… - … Applications of Artificial …, 2024 - Elsevier
Recently, condition monitoring (CM) and fault detection and diagnosis (FDD) techniques for
rotating machinery (RM) have witnessed substantial advancements in recent decades …

Infrared thermography-based fault diagnosis of induction motor bearings using machine learning

A Choudhary, D Goyal, SS Letha - IEEE Sensors Journal, 2020 - ieeexplore.ieee.org
Bearing is one of the most crucial parts in induction motor (IM) as a result there is a constant
call for effective diagnosis of bearing faults for reliable operation. Infrared thermography …

An intelligent fault diagnosis method for rotor-bearing system using small labeled infrared thermal images and enhanced CNN transferred from CAE

H Zhiyi, S Haidong, Z Xiang, Y Yu… - Advanced Engineering …, 2020 - Elsevier
Despite deep learning models can largely release the pressure of manual feature
engineering in intelligent fault diagnosis of rotor-bearing systems, their performance mostly …

Fault diagnosis of a rotor-bearing system under variable rotating speeds using two-stage parameter transfer and infrared thermal images

H Shao, W Li, M Xia, Y Zhang, C Shen… - IEEE Transactions …, 2021 - ieeexplore.ieee.org
Current fault diagnosis methods for rotor-bearing systems are mostly based on analyzing the
vibration signals collected at steady rotating speeds. In those methods, the data collected …

Principal component analysis approach for detecting faults in rotary machines based on vibrational and electrical fused data

M Elsamanty, A Ibrahim, WS Salman - Mechanical Systems and Signal …, 2023 - Elsevier
Rotating machines are frequently used in industrial applications. However, due to their
severity, mechanical failures such as rotor imbalance, shaft imbalance, pulley imbalance …

Machine Learning‐Based Fault Diagnosis of Self‐Aligning Bearings for Rotating Machinery Using Infrared Thermography

A Mehta, D Goyal, A Choudhary… - Mathematical …, 2021 - Wiley Online Library
Bearings are considered as indispensable and critical components of mechanical
equipment, which support the basic forces and dynamic loads. Across different condition …

Predictive maintenance of power substation equipment by infrared thermography using a machine-learning approach

I Ullah, F Yang, R Khan, L Liu, H Yang, B Gao, K Sun - Energies, 2017 - mdpi.com
A variety of reasons, specifically contact issues, irregular loads, cracks in insulation,
defective relays, terminal junctions and other similar issues, increase the internal …

Predictive monitoring of incipient faults in rotating machinery: a systematic review from data acquisition to artificial intelligence

K Saini, SS Dhami, Vanraj - Archives of Computational Methods in …, 2022 - Springer
Predictive maintenance is one of the major tasks in today's modern industries. All rotating
machines consisting of rotating elements such as gears, bearings etc are considered as the …