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  4. Model-based development of health monitoring functions for aircraft hydraulic systems
 
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Model-based development of health monitoring functions for aircraft hydraulic systems

Publikationstyp
Conference Paper
Date Issued
2014-02-26
Sprache
English
Author(s)
Poole, Kevin  
Thielecke, Frank  
Mädiger, Cornelia  
Institut
Flugzeug-Systemtechnik M-7  
TORE-URI
http://hdl.handle.net/11420/7504
Article Number
FPMC2013-4406, V001T01A003
Citation
Proceedings of the ASME/BATH Symposium on Fluid Power and Motion Control - 2013 : presented at ASME/BATH 2013 Symposium on Fluid Power and Motion Control, October 6 - 9, 2013, Sarasota, Florida, USA / sponsored by the Fluid Power Systems and Technology Division, ASME. [Jointly organized by the University of Bath and the American Society of Mechanical Engineers (ASME). General co-chairs Monika Ivantysynova ...]. - New York, NY : ASME, 2014. - Paper No: FPMC2013-4406, V001T01A003, 11 Seiten
Contribution to Conference
ASME/BATH 2013 Symposium on Fluid Power and Motion Control  
Publisher DOI
10.1115/FPMC2013-4406
Scopus ID
2-s2.0-84899797600
Publisher
ASME
Unforeseen failures of hydraulic power generation systems can cause costly operation interruptions of aircraft. To overcome this, a health monitoring of the system components is desirable but not yet available. In this paper, a method is presented that allows a model-based development of such a capability. This method uses physics-based models of system components in order to derive their behavior at considered fault modes with several extents. The gained knowledge is transferred into a model of the entire hydraulic system. This model is used to determine the fault effects on the system states in order to find candidate positions for sensors. The method allows finding an optimal set of sensors that enables the detection and isolation of system component faults. The system model is used further for the creation of a simplified steady-state nominal model, which is required for feature generation. On the basis of these features, support vector machines are trained for fault detection and isolation as well as the diagnosis of the actual fault extent. The developed health monitoring functions are validated on a test rig.
Subjects
Aircraft hydraulic system
Health monitoring
Model-based
Sensor placement
Support vector machine
DDC Class
600: Technik
620: Ingenieurwissenschaften
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