A new breed of metamaterials for health of engineering structures

What is it about?

Highlights • An ultra-sensitive contactless monitoring technique is presented. • Spoof localized surface plasmons- a new breed of metamaterials is proposed. • Evanescence of surface waves is utilized for monitoring deformations. • Transmitted signals are measured in near-field of a resonator.

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Why is it important?

In the recent past, the structural health monitoring (SHM) using various smart materials are in demand due to several reasons. These include (i) continuous increase in construction/manufacturing activity, (ii) demand in lifespan increase of the existing engineering structures, and (iii) never ending thrive to modernize existing/traditional SHM technologies. However, there are several existing issues of smart materials, such as sensor size, signal inaccuracies, low noise to signal ratios and sensitivity limitations that need improvement. Hence, a continuous thrive exists for newer materials and their suitability to improve SHM technologies for engineering. The arrival of electromagnetic (EM) radiation based metamaterials has raised the curiosity due to its rapid measuring speeds, sensitivity, and remote sensing ability. Metamaterial designs are applied often in physics and the sciences but are seldom in engineering. In this paper, an ultra-sensitive contactless monitoring technique which comprises of near-field intensity measurement of surface EM waves in a special patch known as surface localized spoof plasmon (LSP) structure is presented. The principle involves the EM wave application in the radio frequency range that can be extremely localized at the interface of a metal and the dielectric medium (air) of the LSP structure. This EM intensity decays exponentially away from the interface, resulting in the nonlinear response to deformation, suitable for the health inspection of engineering structures. Its suitability for load monitoring in the transverse direction of an engineering beam is verified for two different boundary conditions by a root mean square deviation (RMSD) index.