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Real-time detection of bearing faults through a hybrid WTMP analysis of frequency-related states
I. Bouaissi, A. Rezig, A. Laib, A. Djerdir, O. Guellout, S. Touati and A. N’diaye International Journal of Dynamics and Control 12(11) 3947 (2024) https://doi.org/10.1007/s40435-024-01468-7
The Intelligent Monitoring Technology for Machining Thin-Walled Components: A Review
Vibration-Based Fault Diagnosis of Broken Impeller and Mechanical Seal Failure in Industrial Mono-Block Centrifugal Pumps Using Deep Convolutional Neural Network
Convolutional Neural networks based on parallel multi-scale pooling branch: A transfer diagnosis method for mechanical vibrational signal with less computational cost
Classification of spring strain signals for road classes using Hilbert–Huang transform
Y. S. Kong, S. Abdullah and S. S. K. Singh Journal of the Brazilian Society of Mechanical Sciences and Engineering 44(3) (2022) https://doi.org/10.1007/s40430-022-03390-5
Improving the visualization of rainfall trends using various innovative trend methodologies with time–frequency-based methods
Bearing fault diagnostics using EEMD processing and convolutional neural network methods
Iskander Imed Eddine Amarouayache, Mohamed Nacer Saadi, Noureddine Guersi and Nadir Boutasseta The International Journal of Advanced Manufacturing Technology 107(9-10) 4077 (2020) https://doi.org/10.1007/s00170-020-05315-9
Condition Monitoring of Bearing Faults Using the Stator Current and Shrinkage Methods
Oscar Duque-Perez, Carlos Del Pozo-Gallego, Daniel Morinigo-Sotelo and Wagner Fontes Godoy Energies 12(17) 3392 (2019) https://doi.org/10.3390/en12173392
Study on a Novel Fault Diagnosis Method Based on VMD and BLM