Multistability phenomenon in signal processing, energy harvesting, composite structures, and metamaterials: A review
Multistability is the phenomenon of multiple coexistent stable states, which are highly
sensitive to perturbations, initial conditions, system parameters, etc. Multistability has been …
sensitive to perturbations, initial conditions, system parameters, etc. Multistability has been …
[PDF][PDF] A survey of predictive maintenance: Systems, purposes and approaches
This paper provides a comprehensive literature review on Predictive Maintenance (PdM)
with emphasis on system architectures, purposes and approaches. In industry, any outages …
with emphasis on system architectures, purposes and approaches. In industry, any outages …
Unknown fault feature extraction of rolling bearings under variable speed conditions based on statistical complexity measures
As the main transmission components of rotating machinery, rolling bearings have important
research significance for fault diagnosis and state detection. However, the operating …
research significance for fault diagnosis and state detection. However, the operating …
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 …
Applications of stochastic resonance to machinery fault detection: A review and tutorial
Fault detection is a key tool to ensure the safety and reliability of machinery. In machinery
fault detection, signal processing methods are extensively applied to extract fault …
fault detection, signal processing methods are extensively applied to extract fault …
A second-order stochastic resonance method enhanced by fractional-order derivative for mechanical fault detection
Stochastic resonance (SR), as a noise-enhanced signal processing tool, has been
extensively investigated and widely applied to mechanical fault detection. However …
extensively investigated and widely applied to mechanical fault detection. However …
Review of bridge structural health monitoring based on GNSS: From displacement monitoring to dynamic characteristic identification
X Wang, Q Zhao, R **, C Li, G Li - IEEE Access, 2021 - ieeexplore.ieee.org
Deformation monitoring and dynamic characteristic analysis of bridge structures are the vital
and basic requirements for the safe operation of bridges. In recent years, Global Navigation …
and basic requirements for the safe operation of bridges. In recent years, Global Navigation …
Bearing fault diagnosis using lightweight and robust one-dimensional convolution neural network in the frequency domain
M Hakim, AAB Omran, JI Inayat-Hussain, AN Ahmed… - Sensors, 2022 - mdpi.com
The massive environmental noise interference and insufficient effective sample degradation
data of the intelligent fault diagnosis performance methods pose an extremely concerning …
data of the intelligent fault diagnosis performance methods pose an extremely concerning …
Sound-aided vibration weak signal enhancement for bearing fault detection by using adaptive stochastic resonance
Adaptive stochastic resonance (ASR) has been proven effective in enhancing weak periodic
signals that are submerged in heavy background noise. Given such benefit, ARS has also …
signals that are submerged in heavy background noise. Given such benefit, ARS has also …
A novel stochastic resonance model based on bistable stochastic pooling network and its application
W Zhang, P Shi, M Li, D Han - Chaos, Solitons & Fractals, 2021 - Elsevier
Analysing the vibration and sound signals of machine components is the primary approach
for machine condition monitoring and fault diagnosis. However, due to the special working …
for machine condition monitoring and fault diagnosis. However, due to the special working …