Latest Research in Fault Detection and Control Systems

Top Research Topics in Fault Detection and Control Systems

• Machine Fault Diagnosis Techniques — 18 papers
• Fault Detection and Control Systems — 1 papers
• Advanced Multi-Objective Optimization Algorithms — 1 papers

Highest-Cited Papers

1. Multi-scale physics-informed reinforcement learning method for bearing fault diagnosis under data scarcity
2. Multi-sensor data-driven intelligent product interaction fault self-diagnosis system
3. HabitOSR: Research on the Habit‐Formation Mechanism and Method for Prioritized Unknown Fault Identification in Open Set Bearing Diagnosis
4. Progressive Cross-Model distillation with heterogeneous synergistic classifier for Few-Shot bearing fault diagnosis
5. An Enhanced Hybrid Feature Integration and Boosted Learning Framework for Accurate Diagnostics of Automotive Clutch Systems
6. Non-stationary Compensated Multi-current Pattern (NCMP): A novel image-based motor fault diagnosis framework
7. Toward regulation-friendly bearing fault diagnosis via structural embedding preserving machine unlearning
8. Early fault diagnosis of petrochemical rotor imbalance based on multi-feature under asymmetry
9. Transfer learning-based fault diagnosis of wind turbine high-speed shaft bearings using CWRU pretraining and public run-to-failure data
10. A dual-enhanced generative framework for zero-shot bearing compound fault diagnosis
11. Stage-Aware Multi-Task Learning with Causal Degradation-Prior Fusion for Remaining Useful Life Prediction
12. Adaptive Knowledge Fusion via Dynamic Stacking for Surrogate-Assisted Transfer Optimization
13. Progressive Attention-Guided Two-Stage Transfer Learning for Few-Shot Cross-Condition Bearing Fault Diagnosis
14. A noise-robust over-sampling method for imbalanced transmission production data classification
15. Multi-Scale Attention Conditional Domain Adaptation for Electric Control Valve Fault Diagnosis Under Variable Working Conditions
16. Semantic knowledge transfer framework for wind turbine gearbox compound fault diagnosis via zero-shot learning
17. Cross-Condition Fault Diagnosis of Crane Slewing Bearings Based on a Lightweight Domain-Adaptive Graph Convolutional Network
18. Run-Disjoint Few-Shot XGBoost Framework for Compound Fault Diagnosis of Induction Motors
19. Fault Diagnosis in an Induction‐Motor‐Driven Rotating Machinery Test Rig Under Unseen Operating Loads Using Multimodal Fusion and Multiagent Deep Reinforcement Learning
20. Wavelet-based subdomain-enhanced multi-source domain adaptive network for bearing fault diagnosis