A deep learning method for bearing fault diagnosis based on cyclic spectral coherence and convolutional neural networks
Accurate fault diagnosis is critical to ensure the safe and reliable operation of rotating
machinery. Data-driven fault diagnosis techniques based on Deep Learning (DL) have …
machinery. Data-driven fault diagnosis techniques based on Deep Learning (DL) have …
Applications of robust statistics for cyclostationarity detection in non-Gaussian signals for local damage detection in bearings
Signals with periodic characteristics are ubiquitous in real-world applications. One of these
areas is condition monitoring, where the vibration signals from rotating machines naturally …
areas is condition monitoring, where the vibration signals from rotating machines naturally …
A Rolling Bearing Fault Diagnosis Method via 2D Feature Map of CSCoh After Denoising and MSCNN Under Different Conditions
X Chen, W Lou, W Zhao, G Yang… - Journal of Vibration …, 2024 - journals.sagepub.com
The vibration signal of rolling bearing is interfered by the coupling of other various
components and environment, which brings challenges to effective feature expression and …
components and environment, which brings challenges to effective feature expression and …
Health condition estimation of bearings with multiple faults by a composite learning-based approach
U Inyang, I Petrunin, I Jennions - Sensors, 2021 - mdpi.com
Bearings are critical components found in most rotating machinery; their health condition is
of immense importance to many industries. The varied conditions and environments in …
of immense importance to many industries. The varied conditions and environments in …
[PDF][PDF] Multi-label fault diagnosis based on convolutional neural network and cyclic spectral coherence
Rotating machines are widely used in manufacturing industry, where sudden failures of key
components such as bearings may lead to unexpected breakdown of machines and cause …
components such as bearings may lead to unexpected breakdown of machines and cause …