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A Review of Fault Diagnosis Techniques Applied to Aircraft Air Data Sensors

Authors: Lucas Lima Lopes, Louise Travé-Massuyès, Carine Jauberthie, and Guillaume Alcalay

Published in: OASIcs, Volume 125, 35th International Conference on Principles of Diagnosis and Resilient Systems (DX 2024)


Abstract
Air data sensors provide essential measurements to ensure the availability of autopilot and to maintain aircraft performance, flight envelope protection and optimal aerodynamic surfaces control laws. The importance of these sensors imply the existence of embedded fault tolerance features, mainly represented by hardware redundancy. The latter is prone to fail in case of common fault of multiple sensors, especially if the faults are coherent and simultaneous. Increasing the robustness of fault detection and isolation (FDI) techniques for air data sensors to the aforementioned conditions is essential for the development of more autonomous aircraft, reducing crew workload and guaranteeing flight protections under adverse conditions. This paper reviews recent works on Air Data System (ADS) FDI, assessing proposed model, data and signal-driven approaches. We finally argue in favor of data-driven and hybrid approaches for the development of virtual sensors and semi-supervised anomaly detectors, offering an overview of ways forward.

Cite as

Lucas Lima Lopes, Louise Travé-Massuyès, Carine Jauberthie, and Guillaume Alcalay. A Review of Fault Diagnosis Techniques Applied to Aircraft Air Data Sensors. In 35th International Conference on Principles of Diagnosis and Resilient Systems (DX 2024). Open Access Series in Informatics (OASIcs), Volume 125, pp. 3:1-3:20, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)


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@InProceedings{limalopes_et_al:OASIcs.DX.2024.3,
  author =	{Lima Lopes, Lucas and Trav\'{e}-Massuy\`{e}s, Louise and Jauberthie, Carine and Alcalay, Guillaume},
  title =	{{A Review of Fault Diagnosis Techniques Applied to Aircraft Air Data Sensors}},
  booktitle =	{35th International Conference on Principles of Diagnosis and Resilient Systems (DX 2024)},
  pages =	{3:1--3:20},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-356-0},
  ISSN =	{2190-6807},
  year =	{2024},
  volume =	{125},
  editor =	{Pill, Ingo and Natan, Avraham and Wotawa, Franz},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.DX.2024.3},
  URN =		{urn:nbn:de:0030-drops-220957},
  doi =		{10.4230/OASIcs.DX.2024.3},
  annote =	{Keywords: air data, FDI, aeronautics, review, survey, diagnostics, fault}
}
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