Transfer learning algorithms for bearing remaining useful life prediction: A comprehensive review from an industrial application perspective
Accurate remaining useful life (RUL) prediction for rolling bearings encounters many
challenges such as complex degradation processes, varying working conditions, and …
challenges such as complex degradation processes, varying working conditions, and …
A review of artificial intelligence methods for condition monitoring and fault diagnosis of rolling element bearings for induction motor
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 …
machinery (RM) have critical importance for early diagnosis to prevent severe damage of …
Convolutional neural network based bearing fault diagnosis of rotating machine using thermal images
The bearings are the crucial components of rotating machines in an industrial firm.
Unplanned failure of these components not only increases the downtime, but also leads to …
Unplanned failure of these components not only increases the downtime, but also leads to …
Multi-input CNN based vibro-acoustic fusion for accurate fault diagnosis of induction motor
Induction motor (IM) is a highly efficient prime mover in industrial applications. To maintain
an uninterrupted operation, accurate fault diagnosis system of IM is required. It can help to …
an uninterrupted operation, accurate fault diagnosis system of IM is required. It can help to …
Fault detection and diagnosis in electric motors using 1d convolutional neural networks with multi-channel vibration signals
RFR Junior, IA dos Santos Areias, MM Campos… - Measurement, 2022 - Elsevier
Fault detection and diagnosis in time series data are becoming mainstream in most
industrial applications since the increase of monitoring sensors in machinery. Traditional …
industrial applications since the increase of monitoring sensors in machinery. Traditional …
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 …
call for effective diagnosis of bearing faults for reliable operation. Infrared thermography …
Sounds and acoustic emission-based early fault diagnosis of induction motor: A review study
O AlShorman, F Alkahatni, M Masadeh… - Advances in …, 2021 - journals.sagepub.com
Nowadays, condition-based maintenance (CBM) and fault diagnosis (FD) of rotating
machinery (RM) has a vital role in the modern industrial world. However, the remaining …
machinery (RM) has a vital role in the modern industrial world. However, the remaining …
Experimental setup for online fault diagnosis of induction machines via promising IoT and machine learning: Towards industry 4.0 empowerment
In recent years, the internet of things (IoT) represents the main core of Industry 4.0 for cyber-
physic systems (CPS) in order to improve the industrial environment. Accordingly, the …
physic systems (CPS) in order to improve the industrial environment. Accordingly, the …
Challenges and opportunities of deep learning models for machinery fault detection and diagnosis: A review
In the age of industry 4.0, deep learning has attracted increasing interest for various
research applications. In recent years, deep learning models have been extensively …
research applications. In recent years, deep learning models have been extensively …
VMD based trigonometric entropy measure: a simple and effective tool for dynamic degradation monitoring of rolling element bearing
A Kumar, CP Gandhi, G Vashishtha… - Measurement …, 2021 - iopscience.iop.org
Early identification of rolling element defects is always a topic of interest for researchers and
the industry. For early fault identification, a simple and effective dynamic degradation …
the industry. For early fault identification, a simple and effective dynamic degradation …