RflyMAD: A Dataset for Multicopter Fault Detection and Health Assessment

TL;DR

The RflyMAD dataset provides a comprehensive collection of multicopter fault data from simulations and real flights, supporting fault detection, diagnosis, and health assessment research with potential for transfer learning applications.

Contribution

This paper introduces RflyMAD, a large open-source dataset for multicopter fault detection and health assessment, combining simulation and real flight data to enhance research and benchmarking.

Findings

Contains 114 GB data with 11 fault types across 6 flight statuses.

Includes 5629 flight cases with diverse simulation and real flight data.

Supports transfer learning between simulation and real flight for fault diagnosis.

Abstract

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.