A review on vibration-based condition monitoring of rotating machinery

M Tiboni, C Remino, R Bussola, C Amici - Applied Sciences, 2022 - mdpi.com
Monitoring vibrations in rotating machinery allows effective diagnostics, as abnormal
functioning states are related to specific patterns that can be extracted from vibration signals …

Deep learning aided data-driven fault diagnosis of rotatory machine: A comprehensive review

S Mushtaq, MMM Islam, M Sohaib - Energies, 2021 - mdpi.com
This paper presents a comprehensive review of the developments made in rotating bearing
fault diagnosis, a crucial component of a rotatory machine, during the past decade. A data …

Acoustic spectral imaging and transfer learning for reliable bearing fault diagnosis under variable speed conditions

MJ Hasan, MMM Islam, JM Kim - Measurement, 2019 - Elsevier
Incipient fault diagnosis of a bearing requires robust feature representation for an accurate
condition-based monitoring system. Existing fault diagnosis schemes are mostly confined to …

Automated bearing fault diagnosis scheme using 2D representation of wavelet packet transform and deep convolutional neural network

MMM Islam, JM Kim - Computers in Industry, 2019 - Elsevier
Bearings are one of the most crucial components in many industrial machines. Effective
bearing fault diagnosis is essential for normal and safe machine operation. Existing fault …

A reliable technique for remaining useful life estimation of rolling element bearings using dynamic regression models

W Ahmad, SA Khan, MMM Islam, JM Kim - Reliability Engineering & System …, 2019 - Elsevier
Induction motors most often fail due to faults in the rolling element bearings. Such failures
can cause long and unscheduled downtime in a production facility, which can result in huge …

A hybrid feature model and deep-learning-based bearing fault diagnosis

M Sohaib, CH Kim, JM Kim - Sensors, 2017 - mdpi.com
Bearing fault diagnosis is imperative for the maintenance, reliability, and durability of rotary
machines. It can reduce economical losses by eliminating unexpected downtime in industry …

Automated detection of sleep stages using deep learning techniques: A systematic review of the last decade (2010–2020)

HW Loh, CP Ooi, J Vicnesh, SL Oh, O Faust… - Applied Sciences, 2020 - mdpi.com
Sleep is vital for one's general well-being, but it is often neglected, which has led to an
increase in sleep disorders worldwide. Indicators of sleep disorders, such as sleep …

[HTML][HTML] Data fusion strategies for energy efficiency in buildings: Overview, challenges and novel orientations

Y Himeur, A Alsalemi, A Al-Kababji, F Bensaali… - Information …, 2020 - Elsevier
Recently, tremendous interest has been devoted to develop data fusion strategies for energy
efficiency in buildings, where various kinds of information can be processed. However …

Bearing fault diagnosis under variable rotational speeds using stockwell transform-based vibration imaging and transfer learning

MJ Hasan, JM Kim - Applied Sciences, 2018 - mdpi.com
In this paper, discrete orthonormal Stockwell transform (DOST)-based vibration imaging is
proposed as a preprocessing step for supporting load and rotational speed invariant …

HUST bearing: a practical dataset for ball bearing fault diagnosis

ND Thuan, HS Hong - BMC research notes, 2023 - Springer
Objectives The rapid growth of machine learning methods has led to an increase in the
demand for data. For bearing fault diagnosis, the data acquisition is time-consuming with …