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A time-frequency spectral amplitude modulation method and its applications in rolling bearing fault diagnosis
As one of the key components in rotating machinery, rolling bearings can affect the running
state of equipment and even cause huge damage. Therefore, various methods have been …
state of equipment and even cause huge damage. Therefore, various methods have been …
Online bearing fault diagnosis using numerical simulation models and machine learning classifications
Digital twin (DT) is the embodiment of the most advanced achievements of the current
simulation technology theory development and the direction of intelligent development in the …
simulation technology theory development and the direction of intelligent development in the …
LN-MRSCAE: A novel deep learning based denoising method for mechanical vibration signals
W Du, L Yang, H Wang, X Gong… - Journal of Vibration …, 2024 - journals.sagepub.com
Vibration signals are used to monitor the running state of mechanical equipment, but always
suffer from a lot of noise in the acquisition process. In order to eliminate noise interference …
suffer from a lot of noise in the acquisition process. In order to eliminate noise interference …
Theoretical analysis and comparison of transient-extracting transform and time-reassigned synchrosqueezing transform
Transient-extracting transform (TET) and time-reassigned synchrosqueezing transform
(TSST) developed under the framework of short-time Fourier transform (STFT) can effectively …
(TSST) developed under the framework of short-time Fourier transform (STFT) can effectively …
Theory, validation, and improvement of four enhancement algorithms for repetitive impulses
Analyzing vibration of rotating machinery signals is a popular methodology derived on the
potent tools provided by cyclostationary process theory. Among them, the autocorrelation …
potent tools provided by cyclostationary process theory. Among them, the autocorrelation …
SVD theory for machine fault detection: A Review
Due to the complex working environment and working conditions of mechanical equipment,
its key components are easily damaged, resulting in a decline in equipment performance …
its key components are easily damaged, resulting in a decline in equipment performance …
Fault diagnosis of bearings in multiple working conditions based on adaptive time-varying parameters short-time Fourier synchronous squeeze transform
Rolling bearings are commonly used components in rotating machinery and play a vital role.
When the bearing fails, if it cannot be found and repaired in time, it will cause great …
When the bearing fails, if it cannot be found and repaired in time, it will cause great …
Feature identification based on cepstrum-assisted frequency slice function for bearing fault diagnosis
C Ma, W Zhang, M Shi, X Zou, Y Xu, K Zhang - Measurement, 2025 - Elsevier
Workplace accidents can be avoided through effective rolling bearing condition detection.
From the perspective of frequency domain, various multi-stage segmentation algorithms …
From the perspective of frequency domain, various multi-stage segmentation algorithms …
[HTML][HTML] Rolling bearing fault diagnosis based on time-frequency compression fusion and residual time-frequency mixed attention network
The traditional rolling bearing diagnosis algorithms have problems such as insufficient
information on time-frequency images and poor feature extraction ability of the diagnosis …
information on time-frequency images and poor feature extraction ability of the diagnosis …
Local-global cooperative least squares support vector machine and prediction of remaining useful life of rolling bearing
Aiming at the inability to accurately predict the remaining useful life of rolling bearings due to
the phased degradation in the bearing degradation process, this paper proposes a local …
the phased degradation in the bearing degradation process, this paper proposes a local …