Ultrasound adds the third dimension to wearable sensors.

This paper presents the latest results from a noncontact ultrasonic rail inspection system developed at the University of California, San Diego (UCSD) under the auspices of the Federal Railroad Administration. Noncontact rail probing is an attractive feature that could potentially allow for new possibilities. The UCSD system utilizes a focused air-coupled transmitter, symmetrically placed air-coupled receivers, and a real-time statistical algorithm to maximize true outliers (defects) and minimize false positives. Two field tests were conducted at the Rail Defect Test Facility of the Transportation Technology Center in Pueblo, Colorado, at test speeds from 1.6 to $24\mathrm{km}/\mathrm{h}$ (1 to $15\mathrm{mi}/\mathrm{h}$ ). The results of these tests, evaluated in terms of probability of detection versus probability of false alarms (receiver operating characteristic curves) indicate a good detection performance at the speeds of 1.6 and $8\mathrm{km}/\mathrm{h}$ , with a much poorer performance at the speeds of 16 and $24\mathrm{km}/\mathrm{h}$ . Possible reasons for the performance degradation at the higher speeds are discussed, and future work aimed at mitigating these issues is proposed.

In structural health monitoring (SHM), using only the existing noise has long been an attractive goal. The advances in understanding cross-correlations in ambient noise in the past decade, as well as new understanding in damage indication and other advanced signal processing methods, have continued to drive new research into passive SHM systems. Because passive systems take advantage of the existing noise mechanisms in a structure, offshore wind turbines are a particularly attractive application due to the noise created from the various aerodynamic and wave loading conditions. Two damage detection methods using a passively reconstructed impulse response function, or Green's function, are presented. Damage detection is first studied using the reciprocity of the impulse response functions, where damage introduces new nonlinearities that break down the similarity in the causal and anticausal wave components. Damage detection and localization are then studied using a matched-field processing technique that aims to spatially locate sources that identify a change in the structure. Results from experiments conducted on an aluminium plate and wind turbine blade with simulated damage are also presented.