Thermographic Laplacian-pyramid filtering to enhance delamination detection in concrete structure

Abstract

Despite decades of efforts using thermography to detect delamination in concrete decks, challenges still exist in removing environmental noise from thermal images. The performance of conventional temperature-contrast approaches can be significantly limited by environment-induced non-uniform temperature distribution across imaging spaces. Time-series based methodologies were found robust to spatial temperature non-uniformity but requires extended period to collect data. A new empirical image filtering method is introduced in this paper to enhance the delamination detection using blob detection method that originated from computer vison. The proposed method employs a Laplacian of Gaussian filter to achieve multi-scale detection of abnormal thermal patterns by delaminated areas. Results were compared with the state-of-the-art methods and benchmarked with time-series methods in the case of handling non-uniform heat distribution issue. Tor further evaluate the performance of the method numerical simulations using transient heat transfer models were used to generate the 'theoretical' noise-free thermal images for comparison. Significant performance improvement was found compared to the conventional methods in both indoor and outdoor tests. This methodology proved to be capable to detect multi-size delamination using single thermal image. It is robust to non-uniform temperature distribution. The limitations were discussed to refine the applicability of the proposed procedure.

A Review of Infrared Thermography for Delamination Detection on Infrastructures and Buildings

“…Thus, the analysis is widely used for infrastructure and building surveys [47,92,93]. However, the analysis tends to be subject to noise due to surroundings and nonuniform heatings [94]. The one-time data analysis includes (a) visual evaluation, (b) thermal contrast, and (c) image processing.…”

“…It is also called time-lapsed thermography [36,75], time-dependent IRT [9], or continuous multiframe image processing [91]. The advantages of this analysis are robust to noise by nonuniform environment conditions [94] and high detectability [82]. It also allows conducting the quantitative assessment of delamination depth [85].…”

Case study on the mineralogical and petrophysical analysis of reinforced concrete slabs of a highway viaduct of the S.G.C. Orte-Ravenna

“…The problems related to viaducts are mainly those connected to the degradation of reinforced concrete for different causes: chemical attacks (chlorides, sulphides, salts) [27][28][29], atmospheric agents (rain, freeze-thaw cycle) [30,31], and intensive use [32]. In this work, thermographic analyses were carried out on the RC slabs sampled to determine the most degraded areas and the depth of the degradation [33,34]. The samples, brought to the laboratories of the University of Ferrara in the form of cylindrical specimens, were subjected to compressive strength tests to analyse the resistance of the material and to perform the microscopy analysis for mineralogical characterization [35].…”

Principal Component Thermography for Defect Detection in Concrete

“…If one considers real conditions in-situ, detection of defects using IRT is hindered by the solar irradiance variations, shading caused by clouds or the surrounding objects, as well as the condition of the concrete’s surface (color variations, texture and possible rubble) [ 25 , 26 , 27 ]. The problem also emerges when IRT is intended to be used in shaded areas or concrete elements that cannot be naturally thermally excited by the Sun.…”