Measurement and Characterisation of a Diffuse Acoustic Field Using a Phased Array

A diffuse acoustic field has been increasingly used to infer temporal changes in the structures, such as early dislocations and microcracking. This study explores three different techniques to characterise acoustic field by using a single ultrasonic phased array. The first two techniques are proposed to measure spatial uniformity of wave field by examining differences in the integral of energy and the maximum energy respectively at multiple inspection locations. The third one is developed to evaluate the degree of phase coherence between propagating waves transmitted sequentially by two neighbouring array elements. The efficacy of these techniques are investigated by examining their metrics on simulations and well-known samples. The results suggest that two selected metrics can be used to quantitatively estimate the diffuse field start time as well as the field size by comparing their value with the idealised diffuse state (15% for the energy integral metric, ηarea and 1 for the phase coherence metric, ηphase) and identifying the convergence start point.

Multiwave Total Focusing Method for Full-Matrix Imaging Using Ultrasonic Phased Array

The imaging range of the traditional total focusing method (TFM) is usually limited by the directivity of excitation of a single wave pattern. In this paper, a multiwave TFM technique is proposed, which uses both compression and shear vertical (SV) waves for detection and imaging simultaneously. Based on this technique, a special ultrasonic transducer for multiwave detection is designed that can balance the excitation amplitude of compression and SV waves. Multiwave TFM uses the compression and SV wave fields generated by the same excitation, and the signals reflected by the two sound fields passing through the discontinuity are received. The signals are respectively processed by TFM according to the compression and SV wave velocities. The two processed signals are shifted and aligned according to the time difference between the compression wave with SV wave propagation, and then added together. Finally, the detection image of the block is obtained. Through simulation and experiments, it is shown that the special transducer can optimize the imaging range and effect of multiwave TFM, and multiwave TFM can effectively detect discontinuities and reduce the rate of missed detection at higher steering angles. The detection results show that the maximum amplitude gain of multiwave TFM relative to TFM can be increased about 6 dB.

Towards Explainable Augmented Intelligence (AI) for Crack Characterization

Crack characterisation is one of the central tasks of NDT&E (the Non-Destructive Testing and Evaluation) of industrial components and structures. These days data necessary for carrying out this task are often collected using ultrasonic phased arrays. Many ultrasonic phased array inspections are automated but interpretation of the data they produce is not. This paper offers an approach to designing an explainable AI (Augmented Intelligence) to meet this challenge. It describes a C code called AutoNDE, which comprises a signal-processing module based on a modified total focusing method that creates a sequence of two-dimensional images of an evaluated specimen; an image-processing module, which filters and enhances these images; and an explainable AI module—a decision tree, which selects images of possible cracks, groups those of them that appear to represent the same crack and produces for each group a possible inspection report for perusal by a human inspector. AutoNDE has been trained on 16 datasets collected in a laboratory by imaging steel specimens with large smooth planar notches, both embedded and surface-breaking. It has been tested on two other similar datasets. The paper presents results of this training and testing and describes in detail an approach to dealing with the main source of error in ultrasonic data—undulations in the specimens’ surfaces.

Probe Standoff Optimization Method for Phased Array Ultrasonic TFM Imaging of Curved Parts

The reliability of the ultrasonic phased array total focusing method (TFM) imaging of parts with curved geometries depends on many factors, one being the probe standoff. Strong artifacts and resolution loss are introduced by some surface profile and standoff combinations, making it impossible to identify defects. This paper, therefore, introduces a probe standoff optimization method (PSOM) to mitigate such effects. Based on a point spread function analysis, the PSOM algorithm finds the standoff with the lowest main lobe width and side lobe level values. Validation experiments were conducted and the TFM imaging performance compared with the PSOM predictions. The experiments consisted of the inspection of concave and convex parts with amplitudes of 0, 5 and 15 λAl, at 12 standoffs varying from 20 to 130 mm. Three internal side-drilled holes at different depths were used as targets. To investigate how the optimal probe standoff improves the TFM, two metrics were used: the signal-to-artifact ratio (SAR) and the array performance indicator (API). The PSF characteristics predicted by the PSOM agreed with the quality of TFM images. A considerable TFM improvement was demonstrated at the optimal standoff calculated by the PSOM. The API of a convex specimen’s TFM was minimized, and the SAR gained up to 13 dB, while the image of a concave specimen gained up to 33 dB in SAR.