Bridge scour evaluation based on ambient vibration

Tzu-Kang Lin*, Yen-Po Wang, Ming Chih Huang, Chen An Tsai

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

Abstract

The vulnerability of bridges to hazards such as earthquakes, wind and floods necessitates special structural characteristics. To guarantee the stability of bridge structures, the precise evaluation of the scour depth of bridge foundation has recently become an important issue, as most of the unexpected damage to or collapse of bridges has been attributed to hydraulic issues. In this paper, a vibration-based bridge health monitoring system that utilizes only the response of superstructure to rapidly evaluate the embedded depth of a bridge column is proposed. To clarify the complex fluid-solid coupling phenomenon, the effects of embedded depth and water level were first verified through a series of static experiments. A confined finite element model simulated by soil spring effects was then established to illustrate the relationship between the fundamental frequency and the embedded depth. Using the proposed algorithm, the health of the bridge is able to be inferred by processing the ambient vibration response of the superstructure. To implement the proposed algorithm, a SHM prototype system monitoring environmental factors such as temperature, water level, and inclination was developed to support on-line processing. The performance of the proposed system was verified by a series of dynamic bridge scour experiments conducted in a laboratory flume and compared with readings from a water-proof camera. The results showed that using the proposed vibration-based bridge health monitoring system, the embedded depth of bridge column during complex scour processes is able to be reliably calculated.

Original languageEnglish
Pages (from-to)1113-1121
Number of pages9
JournalJournal of Vibroengineering
Volume14
Issue number3
StatePublished - 4 Oct 2012

Keywords

  • Bridge scour
  • Short-time fourier transform
  • Structure health monitoring

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