"Drone monitoring data and corresponding fault knowledge"
Abstract
"Contains CSV and JSON knowledge data for drone monitoring, generating corresponding PKL datasets,The dataset includes six classes: one normal state and five fault states, including low voltage fault, wind disturbance fault, load loss fault, accelerometer failure, and gyroscope failure. The dataset supports supervised learning, fault detection and isolation, and explainable diagnosis tasks, and can be integrated with knowledge graphs and expert systems for fault cause tracing. It provides a benchmark for evaluating data-driven and knowledge-enhanced fault diagnosis methods in UAV systems. as well as a PubMed dataset"
Fields of Study & Subjects
Fault Detection and Control Systems
Machine Fault Diagnosis Techniques
Engineering and Test Systems
Publication details
- Journal / source
- IEEE DataPort
- Publication date
- 13 January 2026
- Document type
- Dataset