Ultrasound nondestructive evaluation (NDE) imaging with transducer arrays and adaptive processing

Couplants in Acoustic Biosensing Systems

Acoustic biosensors are widely used in physical, chemical, and biosensing applications. One of the major concerns in acoustic biosensing is the delicacy of the medium through which acoustic waves propagate and reach acoustic sensors. Even a small airgap diminishes acoustic signal strengths due to high acoustic impedance mismatch. Therefore, the presence of a coupling medium to create a pathway for an efficient propagation of acoustic waves is essential. Here, we have reviewed the chemical, physical, and acoustic characteristics of various coupling material (liquid, gel-based, semi-dry, and dry) and present a guide to determine a suitable application-specific coupling medium.

A Second-Generation Voltage-Conveyor-Based Interface for Ultrasonic PVDF Sensors

Exploiting the transmission and reception of low frequency ultrasounds in air is often associated with the innate echolocating abilities of some mammals, later emulated with sophisticated electronic systems, to obtain information about unstructured environments. Here, we present a novel approach for the reception of ultrasounds in air, which exploits a piezopolymer broadband sensor and an electronic interface based on a second-generation voltage conveyor (VCII). Taking advantage of its capability to manipulate both voltage and current signals, in this paper, we propose an extremely simple interface that presents a sensitivity level of about −100 dB, which is in line with commercially available references. The presented results are obtained without any filtration stage. The second-generation voltage conveyor active device is implemented through a commercially available AD844, with a supply voltage of ±15 V.

Machine learning at the interface of structural health monitoring and non-destructive evaluation

While both non-destructive evaluation (NDE) and structural health monitoring (SHM) share the objective of damage detection and identification in structures, they are distinct in many respects. This paper will discuss the differences and commonalities and consider ultrasonic/guided-wave inspection as a technology at the interface of the two methodologies. It will discuss how data-based/machine learning analysis provides a powerful approach to ultrasonic NDE/SHM in terms of the available algorithms, and more generally, how different techniques can accommodate the very substantial quantities of data that are provided by modern monitoring campaigns. Several machine learning methods will be illustrated using case studies of composite structure monitoring and will consider the challenges of high-dimensional feature data available from sensing technologies like autonomous robotic ultrasonic inspection. This article is part of the theme issue 'Advanced electromagnetic non-destructive evaluation and smart monitoring'.

On the Use of the Geometric Median in Delay-and-Sum Ultrasonic Array Imaging

Delay-and-sum algorithms are imaging techniques in nondestructive testing, which form images by summing backpropagated signals. Under this approach, a small number of high-intensity signals, such as those from boundary reflections, may create artifacts that degrade the image and hinder defect detection. This article introduces a probabilistic model of the summation, which explains the origin of this effect and proposes to replace the summation in the imaging algorithm by the more statistically robust geometric median. As demonstrated on an experimental inspection using multiview total focusing method and plane wave imaging, this novel technique effectively suppresses some artifacts, at the expense of an increase in the structural noise amplitude and additional diffraction artifacts at the ends of some structural features. As such, the geometric median provides an alternative imaging approach that may improve the performance in some circumstances.

Sizing of flaws using ultrasonic bulk wave testing: A review

Ultrasonic testing is a non-destructive method that can be used to detect, locate and size flaws. The purpose of this paper is to review techniques that utilise ultrasonic bulk waves to size flaws. Flaws that are embedded within a component (i.e. remote from any surface) as well as flaws growing from inaccessible surfaces are considered. The different available techniques are grouped into the following categories: amplitude, temporal, imaging and inversion. The principles, applications and limitations of the different techniques are covered, as well as approaches to assessing the performance of the techniques. Finally, remaining gaps and challenges in sizing flaws, particularly in an industrial setting, are discussed.

Investigation of synthetic aperture methods in ultrasound surface imaging using elementary surface types

Synthetic aperture imaging methods have been employed widely in recent research in non-destructive testing (NDT), but uptake has been more limited in medical ultrasound imaging. Typically offering superior focussing power over more traditional phased array methods, these techniques have been employed in NDT applications to locate and characterise small defects within large samples, but have rarely been used to image surfaces. A desire to ultimately employ ultrasonic surface imaging for bone surface geometry measurement prior to surgical intervention motivates this research, and results are presented for initial laboratory trials of a surface reconstruction technique based on global thresholding of ultrasonic 3D point cloud data. In this study, representative geometry artefacts were imaged in the laboratory using two synthetic aperture techniques; the Total Focusing Method (TFM) and the Synthetic Aperture Focusing Technique (SAFT) employing full and narrow synthetic apertures, respectively. Three high precision metallic samples of known geometries (cuboid, sphere and cylinder) which featured a range of elementary surface primitives were imaged using a 5MHz, 128 element 1D phased array employing both SAFT and TFM approaches. The array was manipulated around the samples using a precision robotic positioning system, allowing for repeatable ultrasound derived 3D surface point clouds to be created. A global thresholding technique was then developed that allowed the extraction of the surface profiles, and these were compared with the known geometry samples to provide a quantitative measure of error of 3D surface reconstruction. The mean errors achieved with optimised SAFT imaging for the cuboidal, spherical and cylindrical samples were 1.3mm, 2.9mm and 2.0mm respectively, while those for TFM imaging were 3.7mm, 3.0mm and 3.1mm, respectively. These results were contrary to expectations given the higher information content associated with the TFM images. However, it was established that the reduced error associated with the SAFT technique was associated with significant reductions in side lobe levels of approximately 24dB in comparison to TFM imaging, although this came at the expense of reduced resolution and coverage.

Toward Optimal Computation of Ultrasound Image Reconstruction Using CPU and GPU

An ultrasound image is reconstructed from echo signals received by array elements of a transducer. The time of flight of the echo depends on the distance between the focus to the array elements. The received echo signals have to be delayed to make their wave fronts and phase coherent before summing the signals. In digital beamforming, the delays are not always located at the sampled points. Generally, the values of the delayed signals are estimated by the values of the nearest samples. This method is fast and easy, however inaccurate. There are other methods available for increasing the accuracy of the delayed signals and, consequently, the quality of the beamformed signals; for example, the in-phase (I)/quadrature (Q) interpolation, which is more time consuming but provides more accurate values than the nearest samples. This paper compares the signals after dynamic receive beamforming, in which the echo signals are delayed using two methods, the nearest sample method and the I/Q interpolation method. The comparisons of the visual qualities of the reconstructed images and the qualities of the beamformed signals are reported. Moreover, the computational speeds of these methods are also optimized by reorganizing the data processing flow and by applying the graphics processing unit (GPU). The use of single and double precision floating-point formats of the intermediate data is also considered. The speeds with and without these optimizations are also compared.

A sparse reconstruction algorithm for ultrasonic images in nondestructive testing

Ultrasound imaging systems (UIS) are essential tools in nondestructive testing (NDT). In general, the quality of images depends on two factors: system hardware features and image reconstruction algorithms. This paper presents a new image reconstruction algorithm for ultrasonic NDT. The algorithm reconstructs images from A-scan signals acquired by an ultrasonic imaging system with a monostatic transducer in pulse-echo configuration. It is based on regularized least squares using a l₁ regularization norm. The method is tested to reconstruct an image of a point-like reflector, using both simulated and real data. The resolution of reconstructed image is compared with four traditional ultrasonic imaging reconstruction algorithms: B-scan, SAFT, ω-k SAFT and regularized least squares (RLS). The method demonstrates significant resolution improvement when compared with B-scan—about 91% using real data. The proposed scheme also outperforms traditional algorithms in terms of signal-to-noise ratio (SNR).