Abstract
Surface Acoustic Wave inspection is a well-known non-destructive testing technique that receives considerable attention to become implemented as a Structural Health Monitoring system. The current work presents a novel approach to embed Surface Acoustic Wave-based Structural Health Monitoring technology inside additively manufactured components. A capillary network is to be integrated inside the component and Surface Acoustic Wave inspection is then deployed on the free capillary surface during the component’s operation to warn upcoming failures.
Highlights
Surface Acoustic Waves (SAW) or Rayleigh Waves are acoustic waves that propagate along the free surface of a material
Most of the surface acoustic energy is contained in the Rayleigh pulse, which propagates at a constant velocity vR, independent of the frequency
Channels are to be integrated by means of additive manufacturing, of which their inner surfaces are utilized as free surfaces for SAW propagation
Summary
Surface Acoustic Waves (SAW) or Rayleigh Waves are acoustic waves that propagate along the free surface of a material. Most of the surface acoustic energy is contained in the Rayleigh pulse, which propagates at a constant velocity vR, independent of the frequency Their amplitude typically decays exponentially into material with most energy concentrated in a one-wavelength thick waveguide just below the free surface [1,2]. With a shallow penetration depth that decreases with increasing frequency, SAWs are very sensitive to (sub)surface imperfections, such as scratches, cracks, voids, etc These surface imperfections cause both dispersion, i.e. dependency of the phase velocity to the wave frequency and attenuation, providing a fingerprint of the inspected surface [2]. Robustness is improved by embedding the SAW inspection technology into the component, preventing detrimental surface alterations to occur The remainder of this manuscript will present the concept in more detail, describe the initial sensor design, demonstrate the production of the embedded channels and report the initial proof-of-concept results
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