Local Corrosion Monitoring of Prestressed Concrete Strand via Time-Frequency Domain Reflectometry

Su Sik Bang, Seung Hyun Yoon, Yeong Ho Lee, Yun Mook Lim, Yong June Shin

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

Demands for diagnostic and monitoring techniques of corrosions on metallic reinforcements which increase the risk of collapse are rising as the number of aged structures are growing. The visual inspection performed in the regular diagnosis of the structures is insufficient to prevent the danger in advance because the corrosions are mainly generated in the interior. In this paper, we propose a new structural health monitoring method for the local and internal corrosion of the structures via time-frequency domain reflectometry (TFDR). The local corrosion can be detected and be localized by TFDR and two indicators for monitoring the corrosion are introduced. The indicators are verified by monitoring experiments of a local corrosion.

Original languageEnglish
Title of host publication2018 International Conference on Diagnostics in Electrical Engineering, Diagnostika 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538644232
DOIs
Publication statusPublished - 2018 Nov 6
Event13th International Conference on Diagnostics in Electrical Engineering, Diagnostika 2018 - Pilsen, Czech Republic
Duration: 2018 Sept 42018 Sept 7

Publication series

Name2018 International Conference on Diagnostics in Electrical Engineering, Diagnostika 2018

Other

Other13th International Conference on Diagnostics in Electrical Engineering, Diagnostika 2018
Country/TerritoryCzech Republic
CityPilsen
Period18/9/418/9/7

Bibliographical note

Publisher Copyright:
© 2018 IEEE.

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering
  • Safety, Risk, Reliability and Quality

Fingerprint

Dive into the research topics of 'Local Corrosion Monitoring of Prestressed Concrete Strand via Time-Frequency Domain Reflectometry'. Together they form a unique fingerprint.

Cite this