This paper presents an open-source dataset RflyMAD, a Multicopter Abnomal Dataset developed by Reliable Flight Control (Rfly) Group aiming to promote the development of research fields like fault detection and isolation (FDI) or health assessment (HA). The entire 114 GB dataset includes 11 types of faults under 6 flight statuses which are adapted from ADS-33 file to cover more occasions in which the multicopters have different mobility levels when faults occur. In the total 5629 flight cases, the fault time is up to 3283 minutes, and there are 2566 cases for software-in-the-loop (SIL) simulation, 2566 cases for hardware-in-the-loop (HIL) simulation and 497 cases for real flight. As it contains simulation data based on RflySim and real flight data, it is possible to improve the quantity while increasing the data quality. In each case, there are ULog, Telemetry log, Flight information and processed files for researchers to use and check. The RflyMAD dataset could be used as a benchmark for fault diagnosis methods and the support relationship between simulation data and real flight is verified through transfer learning methods. More methods as a baseline will be presented in the future, and RflyMAD will be updated with more data and types. In addition, the dataset and related toolkit can be accessed through https://rfly-openha.github.io/documents/4_resources/dataset.html.

翻译：本文介绍一个开源数据集RflyMAD，即由可靠飞行控制（Rfly）课题组开发的多旋翼异常数据集，旨在推动故障检测与隔离（FDI）及健康评估（HA）等研究领域的发展。该数据集总容量114 GB，涵盖6种飞行状态下的11种故障类型，这些状态基于ADS-33标准文件改编，以覆盖多旋翼在故障发生时具有不同机动能力的更多场景。在总计5629个飞行案例中，故障时间累计达3283分钟，包括2566个软件在环（SIL）仿真案例、2566个硬件在环（HIL）仿真案例以及497个真实飞行案例。由于数据集包含基于RflySim的仿真数据和真实飞行数据，因此能在提升数据数量的同时提高数据质量。每个案例均提供ULog日志、遥测日志、飞行信息及预处理文件，供研究人员使用和校验。RflyMAD数据集可作为故障诊断方法的基准，并通过迁移学习方法验证了仿真数据与真实飞行之间的支持关系。未来将提供更多基线方法，并更新RflyMAD以增加更多数据和故障类型。此外，该数据集及相关工具包可通过https://rfly-openha.github.io/documents/4_resources/dataset.html获取。