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Feature Extraction and Sensor Optimization for Condition Monitoring of Recirculation Fans and Filters
Aircraft Design and Systems Group, Aero Hamburg University of Applied Sciences, Hamburg, Germany.
Aircraft Design and Systems Group, Aero Hamburg University of Applied Sciences, Hamburg, Germany.
2009 (English)Conference paper, Published paper (Refereed)
Abstract [en]

Complex systems are commonly monitored by many sensors. When one of the sensors fails, the current state of the system can not be calculated or the information about the current state is not complete. For that reason sensor failures are one of the main error sources of a system. Thus sensors that deliver significant information about the system state need to be redundant. This paper shows how to calculate the significance of the information that a sensor gives about a system by using modern signal processing and artificial intelligence technologies. It also shows how significant features can be extracted, evaluated from a set of data samples, how difficult it is to find an optimal parameter and sensor set and that it is possible to reduce the size of needed data by 97%. The paper concludes analyzing the results of experiments that show that the methods can classify different errors with a 75% probability.

Place, publisher, year, edition, pages
2009. 121196- p.
Keyword [en]
Feature Extraction, Decision Trees, Air Conditioning, A340
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:liu:diva-105838OAI: oai:DiVA.org:liu-105838DiVA: diva2:711174
Conference
Deutscher Luft- und Raumfahrtkongress, 8-10 September 2009, Aachen, Germany
Available from: 2014-04-09 Created: 2014-04-09 Last updated: 2014-04-14
In thesis
1. Predictive Health Monitoring for Aircraft Systems using Decision Trees
Open this publication in new window or tab >>Predictive Health Monitoring for Aircraft Systems using Decision Trees
2014 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

Unscheduled aircraft maintenance causes a lot problems and costs for aircraft operators. This is due to the fact that aircraft cause significant costs if flights have to be delayed or canceled and because spares are not always available at any place and sometimes have to be shipped across the world. Reducing the number of unscheduled maintenance is thus a great costs factor for aircraft operators. This thesis describes three methods for aircraft health monitoring and prediction; one method for system monitoring, one method for forecasting of time series and one method that combines the two other methods for one complete monitoring and prediction process. Together the three methods allow the forecasting of possible failures. The two base methods use decision trees for decision making in the processes and genetic optimization to improve the performance of the decision trees and to reduce the need for human interaction. Decision trees have the advantage that the generated code can be fast and easily processed, they can be altered by human experts without much work and they are readable by humans. The human readability and modification of the results is especially important to include special knowledge and to remove errors, which the automated code generation produced.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2014. 79 p.
Series
Linköping Studies in Science and Technology. Thesis, ISSN 0280-7971 ; 1655
Keyword
Condition Monitoring, Condition Prediction, Failure Prediction, Decision Trees, Genetic Algorithm, Fuzzy Decision Tree Evaluation, System Monitoring, Aircraft Health Monitoring
National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-105843 (URN)LIU-TEK-LIC-2014:88 (Local ID)978-91-7519-346-5 (ISBN)LIU-TEK-LIC-2014:88 (Archive number)LIU-TEK-LIC-2014:88 (OAI)
Presentation
2014-04-11, A38, Hus A, Campus Valla, Linköpings universitet, Linköping, 10:15 (English)
Opponent
Supervisors
Available from: 2014-04-09 Created: 2014-04-09 Last updated: 2015-07-10Bibliographically approved

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CiteExportLink to record
Permanent link

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Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf