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Simone Di Cataldo
Configurable Embedded Software for Sensors Management and Diagnostic in Avionic Systems.
Rel. Stefano Di Carlo, Alessandro Savino, Luca Schena, Nicola Goffredo. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Elettronica (Electronic Engineering), 2024
Abstract: |
A significant percentage of the complexity in aircraft systems is handled at software level, mainly by embedded systems. Historically, embedded software for engine control systems has been written as a monolithic set of code to acquire, manage and diagnose the behaviour of on-board sensors. This type of design made the software difficult to maintain, reuse and port to different aircraft engine topologies. In recent years, the concept of configurable software has become fundamental in avionics to provide adaptable and flexible solutions to the constantly evolving sensors world. In this study, based on an idea of Avio Aero, a GE Aerospace company, the use of this approach is extended for the development of a software capable of designing and creating highly configurable and interchangeable software components for the management of airborne system sensors. Firstly, research is carried out on a turboprop aircraft engine to identify and catalogue the engine sensors on board and how they can be incorporated into software for our purposes. Then, based on an embedded C software architecture for the management of different peripherals of an evaluation board, a software will be developed for the acquisition, conversion, management and diagnosis of avionics sensors. The second phase of the project aims to develop a smart node concept, or rather an environment for a scalable solution that allows, at build time, to configure which sensor to include in the software according to the application, time constraints and target needs. The results allow us to provide useful guidelines for setting up the software environment according to the required specifications and objectives. As a practical result, it is possible to select different types of diagnostics according to specific sensors, to change their parameters, or to meet time constraints imposed by high-level system requirements, simply by changing some parameters in a pre- filled configuration file. |
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Relatori: | Stefano Di Carlo, Alessandro Savino, Luca Schena, Nicola Goffredo |
Anno accademico: | 2023/24 |
Tipo di pubblicazione: | Elettronica |
Numero di pagine: | 88 |
Informazioni aggiuntive: | Tesi secretata. Fulltext non presente |
Soggetti: | |
Corso di laurea: | Corso di laurea magistrale in Ingegneria Elettronica (Electronic Engineering) |
Classe di laurea: | Nuovo ordinamento > Laurea magistrale > LM-29 - INGEGNERIA ELETTRONICA |
Aziende collaboratrici: | GE AVIO S.R.L. |
URI: | http://webthesis.biblio.polito.it/id/eprint/31929 |
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