Ultrasound adds the third dimension to wearable sensors.

In this paper the Semi-Analytical Finite Element (SAFE) method for modeling guided wave propagation is extended to account for linear viscoelastic material damping. Linear viscoelasticity is introduced by allowing for complex stiffness constitutive matrices for the material. Dispersive characteristics of viscoelastic waveguides, such as phase velocity, attenuation, energy velocity and cross-sectional wavestructures are extracted. Knowledge of the above-mentioned dispersive properties is important in any structural health monitoring attempt that uses ultrasonic guided waves for long range inspection. The proposed damped formulation is applied to several waveguides with different mechanical and geometric properties. In particular, a viscoelastic isotropic plate, a railroad track and a pipe are studied.

A sensor diagnostics and validation process that performs in situ monitoring of the operational status of piezoelectric (PZT) active-sensors in structural health monitoring (SHM) applications is presented. Both degradation of the mechanical/electrical properties of a PZT transducer and the bonding defects between a PZT patch and a host structure could be identified by the proposed process. This study also includes the investigation into the effects of the sensor/structure bonding defects on high-frequency SHM techniques, including Lamb wave propagations and impedance methods. It has been found that the effects are significant, modifying the phase and amplitude of propagated waves and changing the measured impedance spectrum. These changes could lead to false indications on the structural conditions without an efficient sensor-diagnostic process. The feasibility of the proposed sensor diagnostics procedure is then demonstrated by analytical studies and experimental examples, where the functionality of the surface-mounted piezoelectric sensors was continuously deteriorated. The proposed process can provide a metric that can be used to determine the sensor functionality over a long period of service time or after an extreme loading event. Further, the proposed method can be useful if one needs to check the operational status of a sensing network right after its installation.

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