Abstract

This work deals with the safety analysis of an air data system (ADS) partially based on synthetic sensors. The ADS is designed for the small aircraft transportation (SAT) community and is suitable for future unmanned aerial vehicles and urban air mobility applications. The ADS’s main innovation is based on estimation of the flow angles (angle-of-attack and angle-of-sideslip) using synthetic sensors instead of classical vanes (or sensors), whereas pressure and temperature are directly measured with Pitot and temperature probes. As the air data system is a safety-critical system, safety analyses are performed and the results are compared with the safety objectives required by the aircraft integrator. The present paper introduces the common aeronautical procedures for system safety assessment applied to a safety critical system partially based on synthetic sensors. The mean time between failures of ADS’s sub-parts are estimated on a statistical basis in order to evaluate the failure rate of the ADS’s functions. The proposed safety analysis is also useful in identifying the most critical air data system parts and sub-parts. Possible technological gaps to be filled to achieve the airworthiness safety objectives with nonredundant architectures are also identified.

Highlights

  • This work describes a safety analysis performed for a simplex air data system partially based on synthetic sensors that is certifiable for civil applications

  • As the present work is funded in the frame of Clean Sky 2, the results are related to the small aircraft transportation (SAT) community but they can be extended to any civil application and to other aircraft categories, such as unmanned aerial vehicles (UAV) and urban air mobility (UAM) vehicles

  • In order to perform a safety analysis, mean time between failures (MTBF) data of the air data system (ADS) sub-parts are evaluated on a statistical basis

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Summary

Introduction

Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. As the avionic background is mature to welcome such innovations on board, synthetic solutions can be replaced or added to physical (or mechanical) sensors in order to analytically increase the system redundancy [9,10,11,12]. Another chance is to use synthetic sensors to monitor physical sensors and to accommodate possible failures [13,14,15]. ADS employs flow angle synthetic sensor based on pretrained neural networks [28] because (1) their determinism (e.g., with respect to Kalman filters) would ease the certification process and (2) low computational effort is required (e.g., with respect to fuzzy approaches [29]).

Safety Analysis Approach
Failure Rate Derivation via Fault Tree Analysis
Reliability Requirements Derivation via Fault Tree Analysis
Flight Phases
Air Data System Description and Functions
Synthetic Sensor Description
Air Data Computer Description
Internal Redundancy Management
ADS Functionalities
MTBF Evaluation
Safety Analysis
Failure Hazard Analysis
ADS Safety Objectives
ADS Safety Performance
Conclusions
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