Reduced surface wave transmission function and neural networks for crack evaluation of concrete structures

Sung Woo Shin, Chung Bang Yun, Hitoshi Furuta, John S Popovics

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

Abstract

Determination of crack depth in field using the self-calibrating surface wave transmission measurement and the cutting frequency in the transmission function (TRF) is very difficult due to variations of the measurement conditions. In this study, it is proposed to use the measured full TRF as a feature for crack depth assessment. A principal component analysis (PCA) is employed to generate a basis of the measured TRFs for various crack cases. The measured TRFs are represented by their projections onto the most significant principal components. Then artificial neural network (ANN) using the PCA-compressed TRFs is applied to assess the crack in concrete. Experimental study is carried out for five different crack cases to investigate the effectiveness of the proposed method. Results reveal that the proposed method can be effectively used for the crack depth assessment of concrete structures.

Original languageEnglish (US)
Title of host publicationSensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2007
DOIs
StatePublished - Nov 1 2007
EventSensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2007 - San Diego, CA, United States
Duration: Mar 19 2007Mar 22 2007

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume6529 PART 1
ISSN (Print)0277-786X

Other

OtherSensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2007
CountryUnited States
CitySan Diego, CA
Period3/19/073/22/07

Keywords

  • Crack depth determination
  • Neural networks
  • Principal component analysis
  • Self-calibrating technique
  • Surface wave transmission

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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  • Cite this

    Shin, S. W., Yun, C. B., Furuta, H., & Popovics, J. S. (2007). Reduced surface wave transmission function and neural networks for crack evaluation of concrete structures. In Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2007 [65291S] (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 6529 PART 1). https://doi.org/10.1117/12.715901