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Model-based fault detection and diagnosis for spacecraft with an application for the SONATE triple cube nano-satellite

Zitieren Sie bitte immer diese URN: urn:nbn:de:bvb:20-opus-198836
  • The correct behavior of spacecraft components is the foundation of unhindered mission operation. However, no technical system is free of wear and degradation. A malfunction of one single component might significantly alter the behavior of the whole spacecraft and may even lead to a complete mission failure. Therefore, abnormal component behavior must be detected early in order to be able to perform counter measures. A dedicated fault detection system can be employed, as opposed to classical health monitoring, performed by human operators, toThe correct behavior of spacecraft components is the foundation of unhindered mission operation. However, no technical system is free of wear and degradation. A malfunction of one single component might significantly alter the behavior of the whole spacecraft and may even lead to a complete mission failure. Therefore, abnormal component behavior must be detected early in order to be able to perform counter measures. A dedicated fault detection system can be employed, as opposed to classical health monitoring, performed by human operators, to decrease the response time to a malfunction. In this paper, we present a generic model-based diagnosis system, which detects faults by analyzing the spacecraft’s housekeeping data. The observed behavior of the spacecraft components, given by the housekeeping data is compared to their expected behavior, obtained through simulation. Each discrepancy between the observed and the expected behavior of a component generates a so-called symptom. Given the symptoms, the diagnoses are derived by computing sets of components whose malfunction might cause the observed discrepancies. We demonstrate the applicability of the diagnosis system by using modified housekeeping data of the qualification model of an actual spacecraft and outline the advantages and drawbacks of our approach.zeige mehrzeige weniger

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Metadaten
Autor(en): Kirill Djebko, Frank Puppe, Hakan Kayal
URN:urn:nbn:de:bvb:20-opus-198836
Dokumentart:Artikel / Aufsatz in einer Zeitschrift
Institute der Universität:Fakultät für Mathematik und Informatik / Institut für Informatik
Sprache der Veröffentlichung:Englisch
Titel des übergeordneten Werkes / der Zeitschrift (Englisch):Aerospace
ISSN:2226-4310
Erscheinungsjahr:2019
Band / Jahrgang:6
Heft / Ausgabe:10
Seitenangabe:105
Originalveröffentlichung / Quelle:Aerospace 2019, 6(10), 105; https://doi.org/10.3390/aerospace6100105
DOI:https://doi.org/10.3390/aerospace6100105
Allgemeine fachliche Zuordnung (DDC-Klassifikation):0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 004 Datenverarbeitung; Informatik
Freie Schlagwort(e):fault detection; model-based diagnosis; nano-satellite
Datum der Freischaltung:28.02.2020
Datum der Erstveröffentlichung:24.09.2019
Open-Access-Publikationsfonds / Förderzeitraum 2019
Lizenz (Deutsch):License LogoCC BY: Creative-Commons-Lizenz: Namensnennung 4.0 International