Data-Efficient Intelligent Fault Detection and Diagnosis for Unmanned Aerial Vehicles

Chuanjiang Li is an Associate Professor at Guizhou University. His research focuses on unmanned aerial vehicles, big data, artificial intelligence, and intelligent maintenance systems. He serves on the committees of the Industrial Big Data and Intelligent Systems Branch of the Chinese Mechanical Engineering Society and the Unmanned Systems Branch of the Chinese Command and Control Society. He has led or contributed to several national-level projects, including the National Key R&D Program and the National Natural Science Foundation of China

• 1. Introduction and Background2. Fundamentals of Intelligent FDD and Data-Efficient Learning3. Fault Detection for UAV Sensors based on CVAE-GAN Model under Zero-shot Conditions4. Metric-Based Fault Diagnosis for UAV Actuators under Few and Imbalanced Data Scenarios5. Generalized Fault Diagnosis based on Meta-Learning for UAV Servo Bearings under Cross-Domain Scenarios6. Transformer-Based Few-Shot Learning for Fault Diagnosis with Noisy Labels and Domain Shifts7. Data Privacy-Preserving Fault Diagnosis Based on Personalized Federated Learning8. Data-Knowledge Driven Intelligent FDD Framework for UAVs