Detection and reconstruction of complex structural cracking patterns with electrical imaging

Abstract

The ability to detect cracks in structural elements is an integral component in the assessment of structural heath and integrity. Recently, Electrical Resistance Tomography (ERT)-based sensing skins have been shown to reliably image progressive surface damage on structural members. However, so far the approach has only been tested in cases of relatively simple crack patterns. Because the spatial resolution of ERT is generally low, it is an open question whether the ERT-based sensing skins are able to image complex structural cracking patterns. In this paper, we test the accuracy of ERT for reconstructing cracking patterns experimentally and computationally. In the computational study, we use a set of numerical simulations that model progressive cracking in a rectangular beam geometry. We also investigate the effect of image reconstruction methods on the crack pattern estimates: In addition to the contemporary image reconstruction method used in the recent sensing skin studies, we test the feasibility of a novel approach where model-based structural prior information on the cracking probability is accounted for in the image reconstruction. The results of this study indicate that ERT-based sensing skins are able to detect and reconstruct complex structural cracking patterns, especially when structural prior information is utilized in the image reconstruction.

An overview of 38 least squares–based frameworks for structural damage tomography

“…θ > 0) avoiding numerical problems with forward operators and ensuring solutions are realistic, (ii) solutions may be bounded between known physical limitations (say 0 < θ < θ impossible ), and (iii) often, constraints result in faster minimization since the solution space is limited to a more feasible set. In the case of imaging structural damage, using for example ERT or QSEI, we can often place realistic constraints based on simple assumptions, such as the realization that damage can only decrease θ, resulting in (0 < θ ≤ θ exp ) (Smyl et al 2018d). Unfortunately, however, the practical implementation of constraints in structural imaging problems is rarely reported.…”

“…To demonstrate the efficacy of one-and two-state ERT, we utilize experimental data from (Smyl et al 2018d). In the experiment, a 152 × 508 × 152 mm lightly-reinforced concrete beam was loaded in three-point bending.…”

“…), and (iv) a combination of (ii) and (iii). In some cases, such as when structural damage processes are not significantly severe and/or complex, the use of (i) and (ii) may be sufficient (Smyl et al 2018d); but, oftentimes, this is not true. The veiled need for (iii) in damage tomography may lie in the fact that damage in structures, either local or distributed, is notoriously nonlinear and difficult to model -although significant progress has been made in multi-scale numerical and constitutive modeling (LLorca et al 2011;Nguyen et al 2011;Liu and Zheng 2010).…”

“…* This model has previously been referred to as nonlinear difference imaging(Smyl et al 2018d;Liu et al 2016Liu et al , 2015a Prepared using sagej.cls…”

Compact Multifunctional Wireless Capacitive Sensor System and Its Application in Icing Detection

“…In addition to the detection of icing, other possible areas of application are, for example, the monitoring of structural elements on buildings with flexible thin skin-like sensors for the detection of damage such as fatigue cracks, corrosion, fractures, material fatigue, or plastic deformations [11][12][13].…”