Air-coupled ultrasonic assessment of concrete rail ties

Sai Kalyan Evani, Agustin Spalvier, John S. Popovics

Research output: Contribution to journalArticlepeer-review

Abstract

This paper investigates a contactless non-destructive evaluation technology for fast and efficient condition assessment of concrete rail ties. Ultrasonic surface waves are generated in rail ties using an air-coupled ultrasonic transmitter and are sensed at another location along the tie using an array of micro-electromechanical system (MEMS) sensors. Concrete rail ties with different types of damage are evaluated. The measured signal data are visualized in time-space (t-x) and frequency-wavenumber (f-k) domains, and four signal parameters are derived. Signal parameters measured from the damaged ties are compared with those from undamaged/healthy ties to generate two- and four-dimensional decision spaces. Threshold decision boundaries separating healthy and damaged rail ties in the decision space are computed using the support vector machine (SVM) algorithm, and the ability of these decision spaces to distinguish between healthy and damaged rail ties is investigated using statistical data analysis. The results demonstrate that high quality signal data are obtained from concrete rail ties using the proposed air-coupled configuration. The four-dimensional decision space, which uses all four signal parameters together, can distinguish between healthy and damaged rail ties with accuracies of around 80 %.

Original languageEnglish (US)
Article number102511
JournalNDT and E International
Volume123
DOIs
StatePublished - Oct 2021

Keywords

  • Contactless
  • Crosstie
  • Evaluation
  • f-k domain
  • Machine learning
  • NDT
  • Nondestructive
  • Support vector machine

ASJC Scopus subject areas

  • Materials Science(all)
  • Condensed Matter Physics
  • Mechanical Engineering

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