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A review of stochastic resonance in rotating machine fault detection
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 …
they can ensure safety and reduce breakdown loss. Weak signal detection is an essential …
Basic research on machinery fault diagnostics: Past, present, and future trends
Machinery fault diagnosis has progressed over the past decades with the evolution of
machineries in terms of complexity and scale. High-value machineries require condition …
machineries in terms of complexity and scale. High-value machineries require condition …
Bearing fault diagnosis via generalized logarithm sparse regularization
Bearing fault is the most common causes of rotating machinery failure. Therefore, accurate
bearing fault identification technique is of tremendous significance. Vibration monitoring has …
bearing fault identification technique is of tremendous significance. Vibration monitoring has …
Time-reassigned multisynchrosqueezing transform for bearing fault diagnosis of rotating machinery
The impulse features in a condition monitoring (CM) signal usually imply the occurrence of a
defect in a rotating machine. To accurately capture the impulse components in a CM signal …
defect in a rotating machine. To accurately capture the impulse components in a CM signal …
A coarse-to-fine decomposing strategy of VMD for extraction of weak repetitive transients in fault diagnosis of rotating machines
Abstract Variational Mode Decomposition (VMD) has attracted much attention and been
used to analyze different kinds of signals, such as mechanical signals, medical data, and …
used to analyze different kinds of signals, such as mechanical signals, medical data, and …
Initial center frequency-guided VMD for fault diagnosis of rotating machines
Variational mode decomposition (VMD), an effective signal decomposing technique, has
attracted considerable attention in recent years. The successful applicability of the VMD …
attracted considerable attention in recent years. The successful applicability of the VMD …
Maximum correlation Pearson correlation coefficient deconvolution and its application in fault diagnosis of rolling bearings
L Qin, G Yang, Q Sun - Measurement, 2022 - Elsevier
Blind deconvolution (BD) has been proved to be an effective tool for recovering periodic
impulses from strong background noise signals is widely used for fault diagnosis of bearings …
impulses from strong background noise signals is widely used for fault diagnosis of bearings …
Improved shift-invariant sparse parsing of mechanical fault based on feature atom
C Han, W Lu, L Cui, L Song… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
In complex operating conditions, the monitoring signals of mechanical equipment are
susceptible to interference from multiple vibration sources and environmental noise …
susceptible to interference from multiple vibration sources and environmental noise …
[HTML][HTML] Intelligent condition monitoring method for bearing faults from highly compressed measurements using sparse over-complete features
Condition classification of rolling element bearings in rotating machines is important to
prevent the breakdown of industrial machinery. A considerable amount of literature has …
prevent the breakdown of industrial machinery. A considerable amount of literature has …
Variable-scale evolutionary adaptive mode denoising in the application of gearbox early fault diagnosis
R Liu, X Ding, Y Zhang, M Zhang, Y Shao - Mechanical Systems and Signal …, 2023 - Elsevier
Due to the influence of gearbox structure complexity, vibration signals are always corrupted
by heavy multiscale noise interference distributed in modulation frequency bands, which …
by heavy multiscale noise interference distributed in modulation frequency bands, which …