DronePropB: Ground Testing Dataset for Commercial Drones with Defective Propellers

The data article presents vibration datasets for faulty propellers collected from over 100 experiments involving various combinations of drones, fault types, fault severities, and operating speeds during ground testing. This dataset is the largest publicly available collection focused on faulty drone propellers. Vibration measurements are obtained using four accelerometers: three onboard accelerometers integrated into the inertial measurement unit (IMU) and an additional highly sensitive piezo accelerometer secured to the drone during ground testing. All identified faults occur while the drone operates normally, without significant performance degradation across all flight phases.本数据论文介绍了面向故障螺旋桨的振动数据集，该数据集源自100余项地面测试实验，涵盖无人机机型、故障类型、故障严重程度与运行转速的多种组合场景。本数据集是目前公开可获取的、聚焦无人机故障螺旋桨的规模最大的同类数据集。振动数据采集采用四台加速度计：三台为集成于惯性测量单元（IMU）的机载加速度计，另一台为地面测试阶段固定于无人机的高灵敏度压电加速度计（piezo accelerometer）。所有已识别的故障均发生于无人机正常运行过程中，且全飞行阶段均未出现显著的性能衰减。

搜集汇总

背景与挑战

背景概述

该数据集是当前公开的最大缺陷螺旋桨振动数据集，包含来自100多个地面测试实验的数据，涉及多种无人机、故障类型、严重程度和操作速度的组合。数据采集使用四个加速度计，确保高精度测量，且所有故障均在无人机正常运行、性能无明显下降的情况下发生。