Biblio

The main limitation of acoustic particle separation for microfluidic application is its low sorting efficiency. This is due to the weak coupling of surface acoustic waves (SAWs) into the microchannel. In this work, we demonstrate bulk acoustic wave (BAW) particle sorting using capacitive micromachined ultrasonic transducers (CMUTs) for the first time. A collapsed mode CMUT was driven in air to generate acoustic pressure within the silicon substrate in the in-plane direction of the silicon die. This acoustic pressure was coupled into a water droplet, positioned at the side of the CMUT die, and measured with an optical hydrophone. By using a beam steering approach, the ultrasound generated from 32 CMUT elements were added in-phase to generate a maximum peak-to-peak pressure of 0.9 MPa. Using this pressure, 10 µm latex beads were sorted almost instantaneously.

Waveguided air-coupled ultrasonic phased arrays offer grating-lobe-free beam forming for many applications such as obstacle detection, non-destructive testing, flow metering or tactile feedback. However, for industrial applications, the open output ports of the waveguide can be clogged due to dust, liquids or dirt leading to additional acoustic attenuation. In previous work, we presented the effectiveness of hydrophobic fabrics as a protection layer for acoustic waveguides. In this work, we created a numerical model of the waveguide including the hydrophobic fabric allowing the prediction of the insertion loss (IL). The numerical model uses the boundary element method (BEM) and the finite element method (FEM) in the frequency domain including the waveguide, the hydrophobic fabric and the finite-sized rigid baffle used in the measurements. All walls are assumed as ideal sound hard and the transducers are ideal piston transducers. The specific flow resistivity of the hydrophobic fabric, which is required for the simulation, is analyzed using a 3D-printed flow pipe. The simulations are validated with a calibrated microphone in an anechoic chamber. The IL of the simulations are within the uncertainties of the measurements. In addition, both the measurements and the simulations have no significant influence on the beamforming capabilities.

Density information has been used as a property of sound to restore objects in a quantitative manner in ultrasound tomography based on backscatter theory. In the traditional method, the authors only study the distorted Born iterative method (DBIM) to create density images using Tikhonov regularization. The downside is that the image quality is still low, the resolution is low, the convergence rate is not high. In this paper, we study the DBIM method to create density images using compressive sampling technique. With compressive sampling technique, the probes will be randomly distributed on the measurement system (unlike the traditional method, the probes are evenly distributed on the measurement system). This approach uses the l1 regularization to restore images. The proposed method will give superior results in image recovery quality, spatial resolution. The limitation of this method is that the imaging time is longer than the one in the traditional method, but the less number of iterations is used in this method.

A lot of research in security of cyber physical systems focus on threat models where an attacker can spoof sensor readings by compromising the communication channel. A little focus is given to attacks on physical components. In this paper a method to detect potential attacks on physical components in a Cyber Physical System (CPS) is proposed. Physical attacks are detected through a comparison of noise pattern from sensor measurements to a reference noise pattern. If an adversary has physically modified or replaced a sensor, the proposed method issues an alert indicating that a sensor is probably compromised or is defective. A reference noise pattern is established from the sensor data using a deterministic model. This pattern is referred to as a fingerprint of the corresponding sensor. The fingerprint so derived is used as a reference to identify measured data during the operation of a CPS. Extensive experimentation with ultrasonic level sensors in a realistic water treatment testbed point to the effectiveness of the proposed fingerprinting method in detecting physical attacks.