"Drone monitoring data and corresponding fault knowledge"

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Authors: Yuan WANG
Cited by: 0

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