Classification of Hardened Cement and Lime Mortar Using Short-Wave Infrared Spectrometry Data

Zohreh Zahiri, Debra F. Laefer, Aoife Gowen

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

This paper evaluated the feasibility of using spectrometry data in the short-wave infrared range (1,300–2,200 nm) to distinguish lime mortar and Type S cement mortar using 42 lab samples (21 lime-based, 21 cement-based) each 40×40×40 mm were created. A Partial Least Squares Discriminant Analysis model was developed using the mean spectra of 28 specimens as the calibration set. The results were tested on the mean spectra of the remaining 14 specimens as a validation set. The results showed that, spectrometry data were able to fully distinguish modern mortars (made with cement) from historic lime mortars with a 100% classification accuracy, which can be very useful in archaeological and architectural conservation applications. Specifically, being able to distinguish mortar composition in situ can provide critical information about the construction history of a structure, as well as to inform an appropriate intervention scheme when historic material needs to be repaired or replaced.

Original languageEnglish (US)
Title of host publicationRILEM Bookseries
PublisherSpringer Netherlands
Pages437-446
Number of pages10
DOIs
StatePublished - 2019

Publication series

NameRILEM Bookseries
Volume18
ISSN (Print)2211-0844
ISSN (Electronic)2211-0852

Keywords

  • Hyperspectral
  • Mortar
  • Partial least square discriminant analysis
  • Short-wave infrared
  • Spectrometry

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Building and Construction
  • Mechanics of Materials

Fingerprint Dive into the research topics of 'Classification of Hardened Cement and Lime Mortar Using Short-Wave Infrared Spectrometry Data'. Together they form a unique fingerprint.

  • Cite this

    Zahiri, Z., Laefer, D. F., & Gowen, A. (2019). Classification of Hardened Cement and Lime Mortar Using Short-Wave Infrared Spectrometry Data. In RILEM Bookseries (pp. 437-446). (RILEM Bookseries; Vol. 18). Springer Netherlands. https://doi.org/10.1007/978-3-319-99441-3_47