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Tests and Analysis of a novel Segmentation method using Measurement Data
University of Cordoba.
University of Cordoba.
Chalmers University of Technology.
Luleå University of Technology, Department of Engineering Sciences and Mathematics, Energy Science.ORCID iD: 0000-0003-4074-9529
2015 (English)Conference paper, Oral presentation only (Refereed)
Abstract [en]

Fault detection in power systems and its diagnosis are highly relevant issues within a power quality scope. Detailed analysis of disturbance recordings, like voltage dips, requires accurate segmentation methods. A joint causal and anti-causal (CaC) segmentation method has been introduced but only been tested with synthetic signals. In this paper, its performance has been analysed with a set of real measurement signals.

Place, publisher, year, edition, pages
2015.
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Research subject
Electric Power Engineering
Identifiers
URN: urn:nbn:se:ltu:diva-38844Local ID: d5be21d1-7817-4aa2-b9e2-da9e064b4d2aOAI: oai:DiVA.org:ltu-38844DiVA: diva2:1012345
Conference
International Conference and Exhibition on Electricity Distribution : 15/06/2015 - 18/06/2015
Note
Godkänd; 2015; 20150625 (matbol)Available from: 2016-10-03 Created: 2016-10-03 Last updated: 2017-11-25Bibliographically approved

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fulltext(468 kB)26 downloads
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CiteExportLink to record
Permanent link

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Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • 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
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  • asciidoc
  • rtf