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2023 | OriginalPaper | Chapter

16. A Vision-Based Quantification Approach for Reinforced Concrete Tunnel Liner Delamination

Authors : Qixiang Tang, Shafique Ahmed, Paul Noyce, Gina Crevello

Published in: Rotating Machinery, Optical Methods & Scanning LDV Methods, Volume 6

Publisher: Springer International Publishing

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Abstract

Infrastructures such as tunnels and bridges in the United States are facing severe degradation. According to the National Tunnel Inventory, the tunnels’ condition needs to be evaluated by a condition state method periodically, which includes detecting and measuring the delamination in the concrete liner due to safety issues. For concrete tunnels in poor conditions, delamination is usually detected using sounding tests (using hammer) and quantified manually (with tape measures and sketch). The quantification process of identified delaminated areas is time-consuming and uneconomical. An alternative approach for quantifying the detected delaminated areas is proposed and validated in this case study. A series of images were extracted from a video recorded from a vehicle traveling through a tunnel. Images were scaled, then converted to binary images, and processed with a pixel-based quantification algorithm. The quantification algorithm can take into consideration the curvature of the surfaces to obtain accurate quantification of surface areas. The delamination dimensions evaluated by the algorithm were verified by the manual quantification method. It is believed that this method could be combined with other structure testing methods for the interdisciplinary perspective of the structural condition.

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Metadata
Title
A Vision-Based Quantification Approach for Reinforced Concrete Tunnel Liner Delamination
Authors
Qixiang Tang
Shafique Ahmed
Paul Noyce
Gina Crevello
Copyright Year
2023
DOI
https://doi.org/10.1007/978-3-031-04098-6_16

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