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This paper presents an open-source dataset RflyMAD, a Multicopter AbnomalDataset developed by Reliable Flight Control (Rfly) Group aiming to promote thedevelopment of research fields like fault detection and isolation (FDI) orhealth assessment (HA). The entire 114 GB dataset includes 11 types of faultsunder 6 flight statuses which are adapted from ADS-33 file to cover moreoccasions in which the multicopters have different mobility levels when faultsoccur. 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 casesfor hardware-in-the-loop (HIL) simulation and 497 cases for real flight. As itcontains simulation data based on RflySim and real flight data, it is possibleto improve the quantity while increasing the data quality. In each case, thereare ULog, Telemetry log, Flight information and processed files for researchersto use and check. The RflyMAD dataset could be used as a benchmark for faultdiagnosis methods and the support relationship between simulation data and realflight is verified through transfer learning methods. More methods as abaseline will be presented in the future, and RflyMAD will be updated with moredata and types. In addition, the dataset and related toolkit can be accessedthrough https://rfly-openha.github.io/documents/4_resources/dataset.html.

RflyMAD: A Dataset for Multicopter Fault Detection and Health Assessment