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Supervision of the Air Loop in the Columbus Module of the International Space Station
Linköping University, Department of Electrical Engineering, Vehicular Systems.
2016 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

Failure detection and isolation (FDI) is essential for reliable operations of complex autonomous systems or other systems where continuous observation or maintenance thereof is either very costly or for any other reason not easily accessible.

Beneficial for the model based FDI is that there is no need for fault data to detect and isolate a fault in contrary to design by data clustering. However, it is limited by the accuracy and complexity of the model used. As models grow more complex, or have multiple interconnections, problems with the traditional methods for FDI emerge.

The main objective of this thesis is to utilise the automated methodology presented in [Svärd, 2012] to create a model based FDI system for the Columbus air loop. A small but crucial part of the life support on board the European space laboratory Columbus.

The process of creating a model based FDI, from creation of the model equations, validation thereof to the design of residuals, test quantities and evaluation logic is handled in this work. Although the latter parts only briefly which leaves room for future work.

This work indicate that the methodology presented is capable to create quite decent model based FDI systems even with poor sensor placement and limited information of the actual design.

[] Carl Svärd. Methods for Automated Design of Fault Detection and Isolation Systems with Automotive Applications. PhD thesis, Linköping University, Vehicular Systems, The Institute of Technology, 2012

Place, publisher, year, edition, pages
2016. , p. 52
Keywords [en]
model based diagnosis, residual generation, structural analysis, causality, automated design
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:liu:diva-133926ISRN: LiTH-ISY-EX--16/5014--SEOAI: oai:DiVA.org:liu-133926DiVA, id: diva2:1065485
Subject / course
Mechanical Engineering
Supervisors
Examiners
Available from: 2017-01-16 Created: 2017-01-16 Last updated: 2017-01-16Bibliographically approved

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CiteExportLink to record
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Citation style
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