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Automated parameter optimization for feature extraction for condition monitoring
Department of Automotive and Aeronautical Engineering, HAW Hamburg.
Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
Hamburg University of Applied Sciences, Aero - Aircraft Design and Systems Group.
Number of Authors: 3
2016 (English)In: 14th IMEKO TC10 Workshop on Technical Diagnostics 2016: New Perspectives in Measurements, Tools and Techniques for Systems Reliability, Maintainability and Safety, Milan, Italy, 27-28 June 2016, 2016, 452-457 p.Conference paper (Refereed)
Abstract [en]

Pattern recognition and signal analysis can be used to support and simplify the monitoring of complex aircraft systems. For this purpose, information must be extracted from the gathered data in a proper way. The parameters of the signal analysis need to be chosen specifically for the monitored system to get the best pattern recognition accuracy. An optimization process to find a good parameter set for the signal analysis has been developed by the means of global heuristic search and optimization. The computed parameters deliver slightly (one to three percent) better results than the ones found by hand. In addition it is shown that not a full set of data samples is needed. It is also concluded that genetic optimization shows the best performance

Place, publisher, year, edition, pages
2016. 452-457 p.
National Category
Other Civil Engineering
Research subject
Operation and Maintenance
Identifiers
URN: urn:nbn:se:ltu:diva-59611ScopusID: 2-s2.0-84985998133OAI: oai:DiVA.org:ltu-59611DiVA: diva2:1033805
Conference
14th IMEKO TC10 Workshop on Technical Diagnostics 2016: New Perspectives in Measurements, Tools and Techniques for Systems Reliability, Maintainability and Safety, Milan, Italy, 27 - 28 June 2016
Available from: 2016-10-10 Created: 2016-10-10 Last updated: 2016-10-26Bibliographically approved

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Galar, Diego
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