Ferrão, Isadora (University of São Paulo), da Silva, Leandro Marcos (University of São Paulo), Almeida da Silva, Sherlon (University of São Paulo), Dezan, Catherine (Université de Bretagne Occidentale), Espes, David (Université de Bretagne Occidentale), Branco, Kalinka Regina Lucas Jaquie Castelo (University of São Paulo)

Intelligent Diagnosis of Engine Failure in Air Vehicles Using the Alpha Dataset

Scheduled for presentation during the Regular Session "Air Vehicle Operations" (ThC3), Thursday, June 8, 2023, 14:40−15:00, Room 464

2023 International Conference on Unmanned Aircraft Systems (ICUAS), June 6-9, 2023, Lazarski University, Warsaw, Poland

This information is tentative and subject to change. Compiled on April 16, 2024

Abstract

Smart cities enable economic and social development through intelligent solutions to various problems, such as access to essential services, mobility, unnecessary energy consumption, security flaws, etc. urban air transport in smart cities. Regarding urban mobility problems, smart cities propose the development of Urban Air Mobility through a safe, sustainable, and affordable air transport system for passenger mobility, cargo delivery, and emergency services within or between metropolitan areas. However, these vehicles are still incipient and their implementation in cities presents challenges such as failures, security, and safety issues. In this sense and also considering a study using the database of the Center for Research and Prevention of Aeronautical Accidents (CENIPA), where engine failures are the main causes of problems in air vehicles, this study was structured using machine learning for the detection of engine failures, intelligently into eVTOLs. The results demonstrate the effectiveness of our technique. Our strategy presents a superior detection, being 21% more effective concerning other recent studies, using the same base of this study, and the same engine failure in aerial vehicles.