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Condition monitoring using pattern recognition techniques on data from acoustic emissions
Dalarna University, School of Technology and Business Studies, Computer Engineering.
Dalarna University, School of Technology and Business Studies, Computer Engineering.
2006 (English)In: ICMLA 2006: 4th International Conference on Machine Learning and Applications, Proceedings, 2006Conference paper, Published paper (Other academic)
Abstract [en]

Condition monitoring applications deploying the usage of impact acoustic techniques are mostly done intuitively by skilled personnel. In this article, a pattern recognition approach is taken to automate such intuitive human skills for the development of more robust and reliable testing methods. The focus of this work is to use the approach as a part of a major research project in the rail inspection area, within the domain of Intelligent Transport Systems. Data from impact acoustic tests made on wooden beams have been used. The relation between condition of the wooden beams and respective sounds they make when struck, has been analyzed experimentally. Features were extracted from the acoustic emissions of wooden beams and were used for pattern classification. Features such as magnitude of the signal, natural logarithm of the magnitude and Mel-frequency cepstral coefficients, yielded good results. The extracted feature vectors were used as input to various pattern classifiers for further pattern recognition task. The effect of using classifiers like Support vector machines and Multi-layer perceptron has been tested and compared. Results obtained experimentally, demonstrate that Support vector machines provide good detection rates for the classification of impact acoustic signals in the NDT domain.

Place, publisher, year, edition, pages
2006.
National Category
Computer and Information Sciences
Research subject
Komplexa system - mikrodataanalys, Automatisk inspektion av järnvägsslipers
Identifiers
URN: urn:nbn:se:du-2707DOI: doi.ieeecomputersociety.org/10.1109/ICMLA.2006.19ISI: 000244477800001OAI: oai:dalea.du.se:2707DiVA, id: diva2:521726
Conference
International Conference on Machine Learning and Applications, , Orlando, USA, December 14-16, 2006
Available from: 2007-04-10 Created: 2007-04-10 Last updated: 2018-01-12Bibliographically approved

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Publisher's full texthttp://www.computer.org/csdl/proceedings/icmla/2006/2735/00/27350003-abs.html

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CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • chicago-author-date
  • chicago-note-bibliography
  • 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