Traffic Events Modeling for Structural Health Monitoring

  • Ugo Vespier
  • Arno Knobbe
  • Joaquin Vanschoren
  • Shengfa Miao
  • Arne Koopman
  • Bas Obladen
  • Carlos Bosma
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7014)

Abstract

Since 2008, a sensor network deployed on a major Dutch highway bridge has been monitoring various structural and environmental parameters, including strain, vibration and climate, at different locations along the infrastructure. The aim of the InfraWatch project is to model the structural health of the bridge by analyzing the large quantities of data that the sensors produce. This paper focus on the identification of traffic events (passing cars/trucks, congestion, etc.). We approach the problem as a time series subsequence clustering problem. As it is known that such a clustering method can be problematic on certain types of time series, we verified known problems on the InfraWatch data. Indeed, some of the undesired phenomena occurred in our case, but to a lesser extent than previously suggested. We introduce a new distance measure that discourages this observed behavior and allows us to identify traffic events reliably, even on large quantities of data.

Keywords

Sensor Network Strain Measurement Structural Health Monitoring Strain Data Subsequence Cluster 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Ugo Vespier
    • 1
  • Arno Knobbe
    • 1
  • Joaquin Vanschoren
    • 1
  • Shengfa Miao
    • 1
  • Arne Koopman
    • 1
  • Bas Obladen
    • 2
  • Carlos Bosma
    • 2
  1. 1.LIACSLeiden UniversityThe Netherlands
  2. 2.Strukton CivielThe Netherlands

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