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Detection of Anomalous Sequences in Crack Data of a Bridge Monitoring

  • Sermad Abbas
  • Roland Fried
  • Jens Heinrich
  • Melanie Horn
  • Mirko Jakubzik
  • Johanna Kohlenbach
  • Reinhard Maurer
  • Anne Michels
  • Christine H. MüllerEmail author
Chapter
Part of the Studies in Classification, Data Analysis, and Knowledge Organization book series (STUDIES CLASS)

Abstract

For estimating the remaining lifetime of old prestressed concrete bridges, a monitoring of crack widths can be used. However, the time series of crack widths show a strong variation mainly caused by temperature and traffic. Additionally, sequences with extreme volatility appear where the cause is unknown. They are called anomalous sequences in the following. We present and compare four methods which were developed in a pilot study and aim to detect these anomalous sequences in the time series. Volatilities caused by traffic should not be detected.

Notes

Acknowledgements

The authors gratefully acknowledge support from the Collaborative Research Center ‘Statistical Modelling of Nonlinear Dynamic Processes’ (SFB 823, B5, C3) of the German Research Foundation (DFG).

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Sermad Abbas
    • 1
  • Roland Fried
    • 1
  • Jens Heinrich
    • 2
  • Melanie Horn
    • 1
  • Mirko Jakubzik
    • 1
  • Johanna Kohlenbach
    • 1
  • Reinhard Maurer
    • 2
  • Anne Michels
    • 1
  • Christine H. Müller
    • 1
    Email author
  1. 1.Department of StatisticsTU University DortmundDortmundGermany
  2. 2.Department of Architecture and Civil EngineeringTU University DortmundDortmundGermany

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