Ultrasound adds the third dimension to wearable sensors.

The general topic of this paper is the passive reconstruction of an acoustic transfer function from an unknown, generally nonstationary excitation. As recently shown in a study of building response to ground shaking, the paper demonstrates that, for a linear system subjected to an unknown excitation, the deconvolution operation between two receptions leads to the Green's function between the two reception points that is independent of the excitation. This is in contrast to the commonly used cross-correlation operation for passive reconstruction of the Green's function, where the result is always filtered by the source energy spectrum (unless it is opportunely normalized in a manner that makes it equivalent to a deconvolution). This concept is then applied to high-speed ultrasonic inspection of rails by passively reconstructing the rail's transfer function from the excitations naturally caused by the rolling wheels of a moving train. A first-generation prototype based on this idea was engineered using noncontact air-coupled sensors, mounted underneath a test railcar, and field tested at speeds up to 80 mph at the Transportation Technology Center (TTC), Pueblo, CO. This is the first demonstration of passive inspection of rails from train wheel excitations and, to the authors' knowledge, the first attempt ever made to ultrasonically inspect the rail at speeds above ∼30 mph (that is the maximum speed of common rail ultrasonic inspection vehicles). Once fully developed, this novel concept could enable regular trains to perform the inspections without any traffic disruption and with great redundancy.

No abstract

Ultrasonic Synthetic Aperture Focus (SAF) techniques are commonly used to image structural defects. In this paper, a variation of SAF based on ideas borrowed from Matched Field Processing (MFP) is evaluated to reduce artifacts and sidelobes of the resulting images. In particular, instead of considering the full RF ultrasonic waveforms for the SAF time backpropagation, only selected features from the waveforms are utilized to form a “data vector” and a “replica” (expected) vector of MFP. These vectors are adaptive for the pair of transmitter-receiver and the focus point. The image is created as a matched filter between these two vectors. Experimental results are shown for an isotropic and homogenous metallic plate with simulated defects, probed by six piezoelectric patches used as receivers or transmitters

The University of California at San Diego (UCSD), under a Federal Railroad Administration (FRA) Office of Research and Development (R&D) grant, is developing a system for high-speed and non-contact rail defect detection. A prototype using an ultrasonic air-coupled guided wave signal generation and air-coupled signal detection, paired with a real-time statistical analysis algorithm, has been realized. This system requires a specialized filtering approach based on electrical impedance matching due to the inherently poor signal-to-noise ratio of air-coupled ultrasonic measurements in rail steel. Various aspects of the prototype have been designed with the aid of numerical analyses. In particular, simulations of ultrasonic guided wave propagation in rails have been performed using a Local Interaction Simulation Approach (LISA) algorithm. The system’s operating parameters were selected based on Receiver Operating Characteristic (ROC) curves, which provide a quantitative manner to evaluate different detection performances based on the trade-off between detection rate and false positive rate. The prototype based on this technology was tested in October 2014 at the Transportation Technology Center (TTC) in Pueblo, Colorado, and again in November 2015 after incorporating changes based on lessons learned.