Assessment of compliance of dimensional tolerances in concrete slabs using TLS data and the 2D continuous wavelet transform

Nisha Puri, Enrique Valero, Yelda Turkan, Frédéric Nicolas Bosché

Research output: Contribution to journalArticle

7 Citations (Scopus)
14 Downloads (Pure)

Abstract

While several concrete waviness assessment methods are being developed to overcome the disadvantages of one assessment method over the other, the sparseness of measurements associated with each method prevents from achieving a better understanding of how elevations and
undulations change across the surface. Assessing waviness over multiple one-dimensional (1D)-survey lines may not accurately reflect the actual condition or waviness of the entire floor. The methodology presented in this paper presents a compliance-checking algorithm for detecting elements where dimensions exceed specified tolerance. It also enables assessment of a concrete surface in two-dimensional (2D) domain using the synergy of Terrestrial Laser Scanning (TLS) and Continuous Wavelet Transform (CWT). 2D CWT analysis provides information not only about the periods of the surface undulation, but also the location of such undulations. The validity of the methodology is established by running a test on point clouds obtained from a warehouse project near Gresham, Oregon. A rigorous comparison between one of the existing floor waviness measurement methods, the waviness index method, and the proposed method is made. The results showed that the proposed methodology delivers accurate results that enable the localization of surface undulations of various characteristic periods. Furthermore, the proposed method is more efficient in terms of time taken for acquiring the measurements, and is, thus, more cost efficient.
Original languageEnglish
Pages (from-to)62-72
JournalAutomation in Construction
Volume94
Early online date21 Jun 2018
DOIs
Publication statusPublished - Oct 2018

Fingerprint Dive into the research topics of 'Assessment of compliance of dimensional tolerances in concrete slabs using TLS data and the 2D continuous wavelet transform'. Together they form a unique fingerprint.

  • Cite this