A Frequency-Aware Residual Decomposition Network for Extracting Incipient Fault Signatures in Rotating Machinery
Open Access
- 12 August 2026
- journal article
- Published by Elsevier in Mechanical Systems and Signal Processing
- Vol. 259
Abstract
No abstract availableThis publication has 31 references indexed in Scilit:
- Integration of dynamic time-varying weighting and interpretable optimization modeling for practical degradation stage assessmentReliability Engineering & System Safety, 2026
- Explainable artificial intelligence based intelligent fault diagnosis: A systematic review from applications to insightsReliability Engineering & System Safety, 2025
- An adaptive fused domain-cycling variational generative adversarial network for machine fault diagnosis under data scarcityInformation Fusion, 2025
- Automated processing of eXplainable Artificial Intelligence outputs in deep learning models for fault diagnostics of large infrastructuresEngineering Applications of Artificial Intelligence, 2025
- IRCNN: A novel signal decomposition approach based on iterative residue convolutional neural networkPattern Recognition, 2024
- An interpretable waveform segmentation model for bearing fault diagnosisAdvanced Engineering Informatics, 2024
- Fully interpretable neural network for locating resonance frequency bands for machine condition monitoringMechanical Systems and Signal Processing, 2022
- Vibration–based Condition Monitoring2021
- A Critical Overview of the “Filterbank-Feature-Decision” Methodology in Machine Condition MonitoringAcoustics Australia, 2021
- Potential, challenges and future directions for deep learning in prognostics and health management applicationsEngineering Applications of Artificial Intelligence, 2020