Latest Research in Machine Fault Diagnosis Techniques
15 research papers · 2026 median publication year
Top Research Topics in Machine Fault Diagnosis Techniques
- Machine Fault Diagnosis Techniques — 15 papers
Highest-Cited Papers
- A novel heterogeneous coupled neuron network and its application in mechanical fault feature enhancement
- Research on gear fault diagnosis of gearboxes under few-shot conditions based on DSCGAN
- Mechanical fault diagnosis under long-tailed data: an improved federated learning method integrating attention, asymmetric convolution, and margin calibration
- Wavelet-patch embedding and two-stage attention fusion for multi-sensor mechanical fault diagnosis
- Fault diagnosis of wind turbine gearboxes using a temporal contrastive learning model integrated with multi-kernel Shiftwise convolution
- Physics-Guided Compositional Diagnosis of Unseen Compound Faults in Variable-Speed Induction Motors
- Physics-Guided Multi-Source Representation Learning for Aero-Engine Bearing Fault Diagnosis under Data Scarcity
- Stable and Compact Diagnostic Signatures for Demagnetization-Related Faults in BLDC/PMSM Drives: Evidence from Two Measurement Campaigns
- Waveform-Prediction Augmentation and Deep Manifold Learning Enable Imbalanced Fault Diagnosis in Rotating Machinery
- Physics-guided adaptive asymmetric wavelet and compact time-frequency representation for single-source cross-condition fault diagnosis of rotating machinery
- A single-source domain generalization method based on frequency-domain statistical priors and class-conditional representation alignment for bearing fault diagnosis
- Multimodal Prompt-Tuning Large Language Model for Machinery Fault Diagnosis with Sound-Vibration Signals
- Interpretable fault diagnosis for multi-sensor systems via a lifting wavelet Siamese transfer network with spatial-channel synergistic attention
- Adaptive Domain-Aligned Multi-Modal Feature Fusion Network for Cross-Speed Fault Diagnosis of Planetary Gearboxes
- Multi-Scale Wavelet-integrated Kolmogorov-Arnold Network (MS-WavKAN) for robust bearing fault diagnosis under harsh industrial noise