A review of stochastic resonance in rotating machine fault detection

S Lu, Q He, J Wang - Mechanical Systems and Signal Processing, 2019‏ - Elsevier
Condition-based monitoring and machine fault detection play important roles in industry as
they can ensure safety and reduce breakdown loss. Weak signal detection is an essential …

Tacholess speed estimation in order tracking: A review with application to rotating machine fault diagnosis

S Lu, R Yan, Y Liu, Q Wang - IEEE Transactions on …, 2019‏ - ieeexplore.ieee.org
Order tracking (OT), which is realized by signal sampling in equal-angle increment
according to the measured rotating speed, is a powerful technique for rotating machine fault …

A combined polynomial chirplet transform and synchroextracting technique for analyzing nonstationary signals of rotating machinery

K Yu, TR Lin, H Ma, H Li, J Zeng - IEEE Transactions on …, 2019‏ - ieeexplore.ieee.org
Time-frequency analysis (TFA) technique is an effective approach to capture the changing
dynamic in a nonstationary signal. However, the commonly adopted TFA techniques are …

The bearing faults detection methods for electrical machines—the state of the art

MA Khan, B Asad, K Kudelina, T Vaimann, A Kallaste - Energies, 2022‏ - mdpi.com
Electrical machines are prone to faults and failures and demand incessant monitoring for
their confined and reliable operations. A failure in electrical machines may cause …

Time-frequency squeezing and generalized demodulation combined for variable speed bearing fault diagnosis

W Huang, G Gao, N Li, X Jiang… - IEEE Transactions on …, 2018‏ - ieeexplore.ieee.org
High-resolution time-frequency representation (TFR) method is effective for signal analysis
and feature detection. However, for variable speed bearing vibration signal, conventional …

A non-linear time–frequency tool for machinery fault diagnosis under varying speed condition

G Yu, X Huang, T Lin, H Dong - Mechanical Systems and Signal …, 2023‏ - Elsevier
Vibration signals acquired from rotating machines operating under varying speed condition
often exhibit strong frequency modulation. Conventional time–frequency analysis …

Weighted cyclic harmonic-to-noise ratio for rolling element bearing fault diagnosis

Z Mo, J Wang, H Zhang, Q Miao - IEEE Transactions on …, 2019‏ - ieeexplore.ieee.org
A novel index termed weighted cyclic harmonic-to-noise ratio (WCHNR) is proposed to
directly evaluate the quality and quantity of harmonics of bearing characteristic frequency …

Condition monitoring and fault diagnosis of motor bearings using undersampled vibration signals from a wireless sensor network

S Lu, P Zhou, X Wang, Y Liu, F Liu, J Zhao - Journal of Sound and Vibration, 2018‏ - Elsevier
Wireless sensor networks (WSNs) which consist of miscellaneous sensors are used
frequently in monitoring vital equipment. Benefiting from the development of data mining …

A novel unsupervised clustering and domain adaptation framework for rotating machinery fault diagnosis

T Kim, S Lee - IEEE Transactions on Industrial Informatics, 2022‏ - ieeexplore.ieee.org
Deep-learning-based fault diagnosis methods require a large number of labeled datasets.
However, considering the changing operating conditions, it is impractical to obtain labeled …

Fault detection for rolling-element bearings using multivariate statistical process control methods

X **, J Fan, TWS Chow - IEEE Transactions on Instrumentation …, 2018‏ - ieeexplore.ieee.org
This paper proposes a new bearing fault detection framework that is based on multivariate
statistical process control methods. In this framework, historical offline normal data are used …