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

Please always quote using this 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.show moreshow less

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Metadaten
Author: Kirill Djebko, Frank Puppe, Hakan Kayal
URN:urn:nbn:de:bvb:20-opus-198836
Document Type:Journal article
Faculties:Fakultät für Mathematik und Informatik / Institut für Informatik
Language:English
Parent Title (English):Aerospace
ISSN:2226-4310
Year of Completion:2019
Volume:6
Issue:10
Pagenumber:105
Source:Aerospace 2019, 6(10), 105; https://doi.org/10.3390/aerospace6100105
DOI:https://doi.org/10.3390/aerospace6100105
Dewey Decimal Classification:0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 004 Datenverarbeitung; Informatik
Tag:fault detection; model-based diagnosis; nano-satellite
Release Date:2020/02/28
Date of first Publication:2019/09/24
Open-Access-Publikationsfonds / Förderzeitraum 2019
Licence (German):License LogoCC BY: Creative-Commons-Lizenz: Namensnennung 4.0 International