Accurate Defect Characterization Research Articles

Improving non-destructive testing methods for detecting cavity damage and internal defects in stone cultural relics: A focus on ultrasonic testing and acoustic tapping technology

This study employs advanced ultrasonic tomography and Grasshopper software to investigate the internal anomalies within stone materials. We aim to enhance the non-destructive testing (NDT) methods with potential applications extending to modern architecture and stone engineering. Cavity damage and internal defects threaten the structural stability of stone cultural relics. Traditional non-destructive testing methods, while practical, have limitations in assessing these relics comprehensively. This paper proposes an enhanced ultrasonic testing method based on mathematical analysis to accurately detect cavity damage in stone cultural relics. We also investigate imaging techniques for internal defects, combining ultrasonic testing with Grasshopper software for efficient and accurate defect characterization. Additionally, we introduce an acoustic tapping method for detecting internal defects in ancient building stones. Verified through field tests and data analysis, this method is non-invasive, accurate, and fast. The process of detecting stone defects using this technology, along with data analysis methods, experimental results, and application effects, are detailed. This research contributes to the improved preservation and restoration of ancient buildings and extends to other fields, such as modern architecture and stone engineering, highlighting its significance in cultural heritage conservation.

Ultrasonic Defect Characterization Using the Scattering Matrix: A Performance Comparison Study of Bayesian Inversion and Machine Learning Schemas.

Accurate defect characterization is desirable in the ultrasonic nondestructive evaluation as it can provide quantitative information about the defect type and geometry. For defect characterization using ultrasonic arrays, high-resolution images can provide the size and type information if a defect is relatively large. However, the performance of image-based characterization becomes poor for small defects that are comparable to the wavelength. An alternative approach is to extract the far-field scattering coefficient matrix from the array data and use it for characterization. Defect characterization can be performed based on a scattering matrix database that consists of the scattering matrices of idealized defects with varying parameters. In this article, the problem of characterizing small surface-breaking notches is studied using two different approaches. The first approach is based on the introduction of a general coherent noise model, and it performs characterization within the Bayesian framework. The second approach relies on a supervised machine learning (ML) schema based on a scattering matrix database, which is used as the training set to fit the ML model exploited for the characterization task. It is shown that convolutional neural networks (CNNs) can achieve the best characterization accuracy among the considered ML approaches, and they give similar characterization uncertainty to that of the Bayesian approach if a notch is favorably oriented. The performance of both approaches varied for unfavorably oriented notches, and the ML approach tends to give results with higher variance and lower biases.

Characterization of defects using ultrasonic arrays: a dynamic classifier approach.

In the field of nondestructive evaluation, accurate characterization of defects is required for the assessment of defect severity. Defect characterization is studied in this paper through the use of the ultrasonic scattering matrix, which can be extracted from the array measurements. Defects that have different shapes are classified into different defect classes, and this essentially allows us to distinguish between crack-like defects and volumetric voids. Principal component analysis (PCA) is used for feature extraction, and several representational principal component subsets are found through exhaustive searching in which quadratic discriminant analysis (QDA) and support vector machine (SVM) are used as the pattern classifiers. Instead of choosing a single optimal classifier, the best classifier is dynamically selected for different measurements by estimating the local classifier accuracy. The proposed approach is validated in simulation and experiments. In simulation, the depths (lengths of the minor axes) of 4441 out of 4636 test samples are measured accurately, and the measurement errors (with respect to the defect size) are below 10%. Arbitrarily shaped rough volumetric defects are identified as ellipses, which are reasonably good matches in shape to the original defects. Experimentally, six subwavelength scatterers are characterized and sized to within 0.14λ.

Experimental validation of an eddy current probe dedicated to the multi-frequency imaging of bore holes

This paper deals with the experimental characterization of an array probe dedicated to the eddy current imaging of sub-millimetric surface breaking defects appearing in bore holes of metallic parts. The probe is constituted of a large inducer generating an uniformly oriented EC flow within the inspected material, and a sensing array probe featuring bobbin coils to sense the radial component of the magnetic field resulting from the eddy currents/defects interactions within the wall of the bore hole. The probe was designed with accurate defect characterization in view, i.e. to provide multi-frequency and high spatial resolution images with a reduced acquisition time, so as to enhance the informative content of the acquired eddy current data. An experimental set-up was build in order to validate the imaging performances of such a probe. A prototype featuring a large inducer and a single sensing coil which can be accurately positioned in the sensing area, has been developed in order to evaluate the sensing performances as well as to study the influence of the sensing array configuration on the imaging performances. The experimental results demonstrate a good sensing ability of the designed probe in the 10–800kHz frequency range, with peak-signal-to-noise ratios higher than 36dB at 10kHz (and 62dB at 800kHz) for defects featuring dimensions as small as 0.4mm×0.2mm×0.2mm. Furthermore, a staggered row arrangement of the sensing array was proposed so as to significantly reduce the error due to the sampling step resulting from the pickup coils geometry (from 35% to less than 9% in the worst case). The experimental evaluation of the probe provides promising prospects for the accurate characterization of defects, by means of advanced multifrequency signal processing algorithms.

Design of Two-Dimensional Ultrasonic Phased Array Transducers

Two-dimensional (2D) phased arrays have the potential to significantly change the way in which engineering components in safety critical industries are inspected. In addition to enabling a three-dimensional (3D) volume of a component to be inspected from a single location, they could also be used in a C-scan configuration. The latter would enable any point in a component to be interrogated over a range of solid angles, allowing more accurate defect characterization and sizing. This paper describes the simulation and evaluation of grid, cross and circular 2D phased array element configurations. The aim of the cross and circle configurations is to increase the effective aperture for a given number of elements. Due to the multitude of possible array element configurations a model, based on Huygens’ principle, has been developed to allow analysis and comparison of candidate array designs. In addition to the element configuration, key issues such as element size, spacing, and frequency are discussed and quantitatively compared using the volume of the 3D point spread function (PSF) as a measurand. The results of this modeling indicate that, for a given number of elements, a circular array performs best and that the element spacing should be less than half a wavelength to avoid grating lobes. A prototype circular array has been built and initial results are presented. These show that a flat bottomed hole, half a wavelength in diameter, can be imaged. Furthermore, it is shown that the volume of the 3D reflection obtained experimentally from the end of the hole compares well with the volume of the 3D PSF predicted for the array at that point.

Theoretical study of the influence of the width of the entrance slit on the contrast of dislocations in X-ray topography by means of simulations

Experimental topographs may be simulated by addition of simulations where one point source is lit on the surface of the crystal. The accuracy of a varying-step integration of Takagi equations is good enough to allow such computations. It is shown that all parts of the contrast are sensitive to the width of the entrance slit and that accurate characterization of defects must take this parameter into account.