Drone monitoring data and corresponding fault knowledge 核心 · 已核验

doi:10.21227/645e-d502

"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"

落地页

https://ieee-dataport.org/documents/drone-monitoring-data-and-corresponding-fault-knowledge

许可证

CC-BY-4.0 (判读置信:inferred)

国内可访问性

国内直连:需登录 (2026-07-11 检测) 代理通道:需登录 (2026-07-11 检测)
检测口径:lychee 双通道单轮探测;「直连超时」表示检测窗口内未完成,系慢或不稳定证据,不构成封锁证据。

设备类型

unmanned_aerial_vehicle

PHM 任务

fault_detection fault_diagnosis

故障工况

传感器