Abstract

This article presents the concept of a chipless radio-frequency identification-based pervasive crack sensing scheme for structural health monitoring (SHM). This scheme includes the design of a novel “smart skin” sensor that can provide contiguous or nondiscretized detection of a structural deformation at any point on its surface. The proposed sensor can identify the growth and propagation of cracks in an area of a building structure. Smart skin sensor has a sensitive microwave structure made of cascaded novel split box resonators coupled to a coplanar waveguide (CPW)-based transmission line. This enables it to offer an uninterrupted crack detection along with the ability to detect multiple structural perturbations simultaneously. The proposed sensor can detect a crack width of as little as 0.5 mm having any orientation; namely, vertical, horizontal, and diagonal cracks. In addition to crack detection, the sensing tag can also provide a distinctive response for moisture ingress into the structure. The article illustrates the theory behind choosing the split box resonator in this sensing scheme followed by the sensor design. It also provides a thorough analysis of the sensor, based on the simulated and experimentally obtained results. Both of these results conform to each other very well, which lays the foundation to use machine learning as future work, in detecting random structural cracks. Such results incorporate many distinguishing features that enable an estimation of crack location and orientations using visual and machine-based classification approaches. The repeatability of the obtained results is also established through the experimental analysis.

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