Distributed cable sensors with memory feature for post-disaster damage assessment

Genda Chen*, Ryan D. McDaniel, David J. Pommerenke, Shishuang Sun

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

Abstract

A new design of distributed crack sensors is presented for the condition assessment of reinforced concrete (RC) structures during and immediately after an earthquake event. This study is mainly focused on the performance of cable sensors under dynamic loading, particularly their ability to memorize the crack history of an RC member. This unique memory feature enables the post-earthquake condition assessment of structural members such as RC columns, in which the earthquake-induced cracks are closed immediately after an earthquake event due to gravity loads and they are visually undetectable. Factors affecting the onset of the memory feature were investigated experimentally with small-scale RC beams under cyclic loading. Test results indicated that both crack width and the number of loading cycles were instrumental in the onset of the memory feature of cable sensors. Practical issues related to dynamic acquisition with the sensors were discussed. The sensors were proven to be fatigue resistant from the shake table tests of RC columns. They continued to show useful signal after the columns can no longer support additional loads.

Original languageEnglish
Article number27
Pages (from-to)236-247
Number of pages12
JournalProceedings of SPIE - The International Society for Optical Engineering
Volume5767
DOIs
Publication statusPublished - 7 Oct 2005
Externally publishedYes
EventNondestructive Evaluation and Health Monitoring of Aerospace Materials, Composites, and Civil Infrastructure IV - San Diego, CA, United States
Duration: 8 Mar 200510 Mar 2005

Keywords

  • Crack detection and localization
  • Nondestructive testing
  • Post-disaster condition assessment
  • Sensors
  • Shake table tests

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

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