Non-destructive Ultrasonic Technique Research Articles

Airframe Icing Properties and Geometry Reconstruction using Ultrasonic Full Waveform Inversion Method

Abstract Recently, Non-destructive Ultrasonic Techniques have been utilized to detect aircraft icing. Traditional methods like ultrasound pulse-echo, guided waves, and optics are unsuitable due to ice’s complex properties and shape. Pulse-echo ultrasound, reliant on surface layer travel time, becomes ineffective with thin ice layers and variable ice properties. This research aimed to reconstruct ice properties and geometry on aircraft surfaces using ultrasonic full waveform inversion (FWI). For simulation COMSOL software is used to verify wave propagation through a nonlinear, thinly layered model. Wave propagation is then modelled using the 2D acoustic equation and finite differential methods, generating synthetic data. The FWI algorithm implemented, utilizes this synthetic data to reconstruct material properties and ice shape. Crucially, ultrasound transducers are discreetly positioned beneath the aircraft skin to non-destructively gather ice information without affecting aerodynamics.

Prediction of axial compressive stresses in ultra-high-performance concrete blocks using non-destructive ultrasonic techniques

The application of ultra-high-performance concrete (UHPC) in civil engineering structures is growing rapidly. On the other hand, previous non-destructive testing (NDT) techniques mainly focused on determining the relationship between the acoustic characteristics and elastic modulus, Poisson's ratio, cracking resistance, and strength. This study presents an experimental approach utilizing ultrasonic techniques to predict the axial compressive stresses in UHPC structures. Both cubic and prismatic UHPC blocks were designed and tested under different compressive axial loading conditions, and their ultrasonic acoustic characteristics were evaluated in detail. Normal strength concrete (NSC) blocks were also included in the investigation for comparison purposes. A detailed account of the tests results is provided, including the relationships between the compressive stresses in UHPC blocks and the typical time- and frequency-domain acoustic parameters. Based on the experimental results, an analytical working stress evaluation method for UHPC components using the ultrasonic acoustic parameters is proposed. It is shown that there is close correlation and high prediction stability between the compressive stress in UHPC blocks and the ultrasonic velocity, which is suggested as the main acoustic parameter for stress detection. The correlation between the acoustic amplitude parameters and concrete compressive stress is also shown to be significant, yet is associated with relatively low prediction stability. Moreover, in comparison with conventional NSC blocks, greater correlation and regularity ratios are observed between the typical acoustic parameters and the axial compressive stress in UHPC specimens. Overall, the analytical models proposed in this study are shown to be in close agreement with the experimental results, and can be used, in conjunction with the ultrasonic NDT techniques, to provide a reliable prediction of the level of compressive stresses in UHPC members.

Identifying grain size in ASTM A36 steel using ultrasonic backscattered signals and machine learning

Ultrasonic nondestructive techniques can be useful tools in the microstructural classification of metallic alloys. Among the most common techniques for characterizing materials, backscattered signal analysis stands out because it does not require a back surface echo. This study classifies five ASTM A36 steel samples with varying grain sizes using ultrasonic waves. For each sample, ultrasound signals were obtained using two ultrasonic array probes with center frequencies of 5 and 10 MHz. An extensive feature engineering process was conducted using the tfresh package in Python, which extracts a wide range of features from time series data, transforming raw ultrasound signals into a structured format. Seven machine learning models were evaluated based on accuracy, precision, recall, and F1 score, with performances ranging from 70 to 100%. The XGBoost model exhibited the best performance with 10 MHz probe signals, achieving 100% accuracy. An additional validation test was conducted to evaluate the models’ generalization capability, considering inter-specimen variabilities. Despite a slight reduction in prediction metrics, the XGBoost model maintained good performance, with accuracy between 89% and 100% across all frequencies. Such findings demonstrate that backscattered grain noise can effectively identify grain sizes provided that an adequate machine learning model is used.

Use of Non-Destructive Ultrasonic Techniques as Characterization Tools for Different Varieties of Wine.

In this work, we have verified how non-destructive ultrasonic evaluation allows for acoustically characterizing different varieties of wine. For this, a 3.5 MHz transducer has been used by means of an immersion technique in pulse-echo mode. The tests were performed at various temperatures in the range 14-18 °C. The evaluation has been carried out studying, on the one hand, conventional analysis parameters (velocity and attenuation) and, on the other, less conventional parameters (frequency components). The experimental study comprised two stages. In the first, the feasibility of the study was checked by inspecting twelve samples belonging to six varieties of red and white wine. The results showed clearly higher ultrasonic propagation velocity values in the red wine samples. In the second, nine samples of different monovarietal wine varieties (Grenache, Tempranillo and Cabernet Sauvignon) were analyzed. The results show how ultrasonic velocity makes it possible to unequivocally classify the grape variety used in winemaking with the Cabernet Sauvignon variety having the highest values and the Grenache the lowest. In addition, the wines of the Tempranillo variety are those that present higher values of the attenuation coefficient, and those from the Grenache variety transmit higher frequency waves.

The influence of the content of phosphates in water on the propagation speed of ultrasonic waves.

The phosphate content of a test sample is one of the indicators of the trophic status of the test water. In this work, an attempt was made to use a non-destructive ultrasonic technique to determine this parameter. For this purpose, a specially prepared measuring station was used, on which distilled water samples with different phosphate contents were tested. Specially prepared samples contained 0, 20, 40, 60, 80 and 100 kg/m3 of phosphates. In addition, tests were carried out on the effect of sample temperature on the values of the characteristic parameter of the wave, in the range from 12 to 30 oC. All tests were carried out using two ultrasonic heads with a wave frequency of 2 MHz. The ultrasonic wave parameter analysed in the study was the propagation speed of the ultrasonic wave. The results obtained indicate that the ultrasonic method is useful for non-destructive evaluation of phosphate content in the sample. Additionally, they show a large influence of the sample temperature on the results read.

Quantitative ultrasonic imaging of weave structure in textile composites

Textile composites owe their desirable mechanical properties to the intricate fabric architecture. However, manufacturing deviations can influence these attributes, significantly affecting their mechanical performance. Thus, ensuring the quality and structural integrity of fabric architectures has become pivotal, leading to the advancement of ultrasonic non-destructive testing techniques. However, existing techniques, primarily tailored for unidirectional laminates, often struggle with weave pattern extraction, given the complex features of fabric laminates. To address this gap, a pulse-echo ultrasound coupled to a 2D analytic-signal analysis is proposed. The 2D analytic-signal methodology autonomously discerns the complex ultrasound features from fabric laminates, streamlining weave pattern analysis. The study showcases ply-by-ply reconstruction of local weave patterns of fabric laminates with nominal layups of [#(0/90)]8 and [#(+45/−45)#(0/90)]5s, respectively. The efficacy of the methodology is ascertained through quantitative metrics, highlighting its innovative potential for through-depth extraction of local weave patterns in a swift and automated manner.

Ultrasonic velocity measurements of backscattered acoustic waves for monitoring the enzymatic coagulation of milk

In this work, the milk coagulation process was monitored by a nondestructive ultrasonic technique. Three analysis methods were used to calculate ultrasonic wave velocity and assess their effectiveness in tracking the physicochemical changes: Cross-correlation, Spectrum ratio, and Smoothed Pseudo-Wigner-Ville transform. The obtained results show a consistency between the velocity measurements made by these three methods, with a steady increase observed during coagulation and both phases are visible. The time-frequency method was most effective, showing a clearer transition between the two phases. This study suggests that non-destructive ultrasonic techniques with time-frequency analysis could be advantageous for monitoring milk coagulation and ensuring dairy product quality.

Modeling of Ultrasonic Flaw Detection Processes in the Task of Searching and Visualizing Internal Defects in Assemblies and Structures

Introduction. Inverse problems are a specific type of tasks where the consequences of phenomena are studied to identify their causes. They are widely used in scientific studies, specifically, those dealing with large amounts of experimental data. In the presented paper, inverse problems in mechanical engineering and structural diagnostics are considered. These areas require precise methods to identify internal defects in various materials, which can be critical to ensure the safety and efficiency of technical structures. Despite the many flaw detection methods available, there is a need for innovative developments that can provide higher accuracy and efficiency. This study integrates different scientific methods and technologies. It opens up new perspectives in nondestructive testing for the detection of internal defects in various materials and structures. Its objective is to develop and implement nondestructive testing methods based on a neural network device to improve the accuracy of defect identification, as well as to build a neural network model and evaluate its effectiveness for the refinement of ultrasonic visualization of internal defects in solid materials. In this regard, the task to be solved is to create a reliable tool for accurate visualization of sizes, shapes, location and orientation of internal defects in various materials.Materials and Methods. The technique of determining the geometric parameters of defects in materials through nondestructive testing is used. The approach combining modeling of ultrasonic wave propagation in acoustic medium and artificial neural network technologies is applied. This approach identifies nonlinear relationships between the geometry of defects and the amplitude-frequency and amplitude-time data obtained during signal analysis. Artificial neural networks are a model that can be trained on examples, which provides for an effective solution to problems that are difficult to express in traditional forms. The study uses the finite difference method in the time domain. It is applied to identify and visualize internal defects in materials using ultrasonic nondestructive testing and convolutional generative neural networks.Results. A convolutional neural network has been developed to visualize internal defects using ultrasonic nondestructive testing techniques. This neural network successfully determines the size of defects, their location, shape and orientation with high accuracy and reliability.Discussion and Conclusion. The authors highlight the key influence of defect size on the accuracy of ultrasonic imaging in various scenarios. The validation of the model for three different cases of defects with different mechanical parameters has shown that for successful visualization of defects, the wavelength of the ultrasonic pulse must be ten times smaller than the size of the defect. When analyzing the impact of defect size on the accuracy of the neural network, it is found that the visualization error increases for defects of smaller size. It has also been found that the relative speed of sound in materials has a greater effect on the accuracy of the method than the relative density of the material. Based on the results obtained by the authors, it can be argued that the developed methods and technical solutions are of great importance for future research in the field of flaw detection. They have significant potential for scientific and practical applications.

Ultrasonic measurement of roller revolution speed for high-speed rolling bearing

The sliding state of the bearing rollers can be identified by measuring the roller revolution speed. At present, the roller revolution speed is mainly approximated by the average speed of the cage, which can be obtained by optical and electric methods. However, there are some bottlenecks in the practical application of these methods. In this study, a non-destructive ultrasonic technique is proposed to measure the high-speed rolling bearings' roller revolution speed. In order to reduce the impact of time-domain noise on the ultrasonic echo pulse signal, autocorrelation analysis and the FFT transform are introduced. The passing frequency of a roller can be more accurately calculated by using the CZT (linear frequency modulation Z transform) spectrum thinning algorithm. This ultrasonic approach's validity is confirmed when compared to the conventional optical method at low speed. Then, in accordance with the theoretical models, the roller slippage at high speed is observed by directly measuring the speed of the roller revolution.

Effect of H3PO4 content and processing temperature on the structure and mechanical properties of porous Si3N4

Open-porous silicon nitride ceramics have been fabricated via low-temperature processing at 1200 °C using phosphoric acid as an inorganic binder and pore-forming agent. A detailed study of the effect of phosphoric acid content on the microstructure development and an in-depth analysis of the influence of the porosity and pore morphology on compressive strength, flexural strength, and notch-root radius corrected fracture toughness has been performed. Further, the progressive evolution of porosity and the amount and type of crystalline phases as a function of processing temperature were studied by intermittent XRD analysis. For the first time, a detailed analysis of the pore structure evolution on the longitudinal elastic constant of the porous samples was studied using a non-destructive ultrasonic technique. The critical H3PO4 content of 40 vol% yielded a homogeneous nanoporous structure that resulted in the best mechanical properties – compressive strength >120 MPa, flexural strength >70 MPa, and a notch-root radius corrected KIC ∼1 MPa m1/2. Despite the low fabrication temperature and economic processing route, the mechanical properties of the fabricated porous samples are comparable to the values for porous Si3N4 reported in the literature.

Methodology of residual strength prediction of composite structures with low-velocity impact damage based on NDT inspections and numerical-experimental CAI testing

One of the most challenging tasks is to evaluate a structural condition and predict a residual strength when damage is present in a composite structure. Such a prediction is usually performed based on experimental destructive testing on specimens, which often does not reflect the geometrical complexity of a component with damage, or based on numerical simulations, which are difficult to parametrize due to the complexity of fracture mechanisms of composite materials. In this paper, we proposed a hybrid methodology based on evaluation of results of the ultrasonic non-destructive testing technique supported with numerical modeling and compression after impact (CAI) tests to evaluate residual strength of glass- and carbon-reinforced polymer composite structures. Based on ultrasonic C-scans processing and incorporation of impact damage shapes in numerical models and further evaluation of the obtained results in the light of CAI tests, the model for the prediction of residual strength in composites was developed.

Noncontact nondestructive ultrasonic techniques for manufacturing defects monitoring in composites: a review

Composite materials are widely used in most industries due to their high specific strength, specific stiffness, and their relatively lighter weight compared to other traditional materials. However, the presence of defects arising from manufacturing processes or during service loads can make these structures more susceptible to a diminished performance. Furthermore, the former defects are inevitable in composite structures, but they can be reduced. Each type of defect requires specific inspection techniques and configurations. In this work, a review of the different types of composites manufacturing processes and their corresponding resultant defects is presented with the various nondestructive evaluation techniques employed for these defects’ characterization. The emphasis of this paper is on ultrasonic inspection and detection techniques for they present high sensitivity to surface/subsurface discontinuities, superior depth of ultrasonic penetration for flaw detection, feasibility on large scales, and instantaneous and detailed images production. Notably, noncontact ultrasonic testing techniques are also reviewed, air-coupled techniques in specific, and highlighted as a fine alternative to conventional contact inspection systems as they reduce the restrictions that coexist with the use of couplants. Moreover, these ultrasonic testing techniques are summarized to show the latest research progress achieved in the field of air-coupled ultrasonic inspection systems for manufacturing defects’ monitoring in composite structures including delamination, porosity, dryness, waviness, and resin lack/excess. Finally, we highlight the type and central frequency of the transducers and experimental results present in literature and obtained in terms of both detection and size of the defects.

Non-destructive detection of disintegrant levels in compressed oral solid dosage forms

Quality issues related to compressed oral solid dosage (OSD) forms, such as tablets, arise during the design, development, and production stages, despite established processes and robust production tools. One of the primary quality concerns is the disintegration properties and drug release profile of immediate-release OSD products, which depend on their micro-texture and micro-viscoelastic properties at the grain level. These properties are influenced by the composition of the formulation, particularly the disintegrant level in the tablet matrix and the porosity of the matrix. In this study, a novel, rapid, non-destructive ultrasonic characterization technique was proposed to correlate the sensitivity of propagating elastic wave speeds, physical/mechanical properties, and the dispersion profile of the OSD material with the disintegrant level (% w/w) in the formulation and the compression force applied during tableting. The proposed characterization framework involves transmitting pressure (longitudinal) and shear (transverse) waves through the OSDs to calculate the speed of sound, which in turn provides information on the apparent Young's and shear moduli. In addition, the attenuation profile of the propagating wave is obtained through dispersion analysis. To investigate the impact of disintegrants and compression force on ultrasonic wave propagation in OSDs, we incorporated seven levels of a frequently used disintegrant. In each formulation, OSDs are compacted in five compaction forces. The sensitivity of wave speeds, physical/mechanical properties, and attenuation profile was observed with each disintegrant and compression force level. The utilization of ultrasonic techniques may present a viable solution for rapid, non-destructive, non-invasive, and cost-effective testing methods required in continuous manufacturing (CM) and real-time release testing (RTRT), and its practical utility in pharmaceutical manufacturing is also discussed.

Effect of thermal fatigue on mechanical properties and microstructure of concrete in constant ambient humidity

The daily and annual temperature differences in mid and high latitudes areas vary greatly, which leads to thermal fatigue deterioration of concrete. The deterioration of concrete properties can also be generated by the cyclic change of humidity in concrete. In the experiment, the thermal fatigue tests of concrete with two strength grades were carried out at the temperature difference of 20 °C, 30 °C, and 40 °C (the initial temperature is 20 °C) under the condition of constant ambient humidity. The macroscopic properties change of concrete such as compressive strength and splitting tensile strength were measured. The microstructure changes of concrete were determined by ultrasonic nondestructive testing technique and mercury intrusion test. The results indicated that thermal fatigue has obvious deterioration effect on concrete. With the increase of temperature difference and cycle number, the strength of concrete decreased dramatically and the decrease of C40 concrete was greater than that of C25 concrete. The splitting tensile strength was more sensitive to thermal fatigue than compressive strength. The ultrasonic wave velocity gradually decreased and the damage factor increased, indicating the internal crack defects of concrete increased. At the same temperature difference, the porosity, total pore volume, average pore diameter, medium pore diameter, and the most probable pore diameter of concrete increased gradually with the increase of the cycle number, while the total pore surface area decreased. The pore structure showed the characteristics of coarsening and the trend of deterioration. The porosity of C40 concrete was less than that of C25 concrete, but the relative change value of porosity was larger, which reveals the internal reason for the strength damage of concrete under thermal fatigue at the microscopic level.

Microstructure and Elastic Properties of Hydroxyapatite/Alumina Nanocomposites Prepared by Mechanical Alloying Technique for Biomedical Applications

Although hydroxyapatite (HA) has exceptional biological qualities that inspire researchers to employ it as an appealing biomaterial for various purposes, its usage in hard tissue replacement applications is severely restricted because of its fragility. In order to create nanocomposites with the necessary mechanical properties for biomedical applications, HA was produced, and various amounts of alumina (Al2O3) were added to it. Additionally, the phase composition of the powdered nanocomposites was examined using the X-ray diffraction (XRD) technique. Crystal sizes, lattice strain, and dislocation density were all estimated as well. In order to measure the produced nanocomposite powders’ physical and elastic characteristics using the Archimedes method and ultrasonic non-destructive technique, they were then pressed and sintered at 1000 °C. The resulting information made it clear that further increases in the weight percentages of Al2O3 resulted in a 10.25, 25.64, and 33.33% reduction in crystal size. As a result of adding more Al2O3-up to 20 weight, percent-the results also showed that this properties-microhardness, compressive strength, Young’s modulus, elastic modulus, bulk modulus, shear modulus, and Poisson’s ratio-were improved by 109, 36.29, 95.5, 100.59, 104.97, 92.84 and 9.5%, respectively. Unfortunately, it increased its porosity by considerable amounts. It might be argued that the generated nanocomposites are favorable for biomedical applications.

Nondestructive analysis of corrosion in ageing hardened AA6351 aluminium alloys

Aluminum alloys have been chosen over other lightweight structural materials because of their advantages regarding strength, long-term durability, and low cost. Aluminum comes under the category of highly reactive metals, where an inherently stable oxide layer can protect against aggressive corrosive conditions. Therefore, this research investigated the application of the ultrasonic nondestructive technique for inspection and monitoring of corrosion behavior of AA6351 heat-treated aluminum alloys. The samples were artificial age hardened at five different conditions. The complementary engineering experiments for materials evaluation included hardness, X-ray diffraction and salt spray tests. Overall findings showed correlations between ultrasonic and destructive data representing a fast, versatile and reliable inspection technique. Furthermore, findings show a significant correlation (>99%), thus supporting the benefits of the multiparametric ultrasonic test for heat treatment inspection and quality control of lightweight structural materials.

UACIS: Uncrewed Aerial Concrete Inspection System

The main challenge to the automation of NDE is the compound problem between the wide variety of NDT (non-destructive technique) available coupled with the diversity of infrastructures to be inspected. In some cases, the identification of flaws may require multiple complementary NDT to assert confidence in the results, adding further complexity to the issue. In this context, developing an automated system applicable to a wide variety of inspection conditions is an arduous task. Yet, targeting a wide range of applications, reducing inspection time or increasing safety are all essential factors to making such development worthwhile. This study aims to achieve the automation or semi-automation of ultrasonic NDT for concrete inspection using a UAV. Two NDT techniques are being considered, Impact Echo and Ultrasonic testing using Dry Point Contact transducers. Challenges regarding the mechanical and electric implementation of the NDT payloads to the UAV as well as the impact of the UAV on the recorded NDT data will be discussed and initial results will be presented.

Investigation of magnetic phase transitions in Ni0.5Cu0.25Zn0.25Fe2-xLaxO4 nanoferrites using magnetic and in-situ ultrasonic measurements

In this study, Ni0.5Cu0.25Zn0.25Fe2-xLaxO4 (x = 0.000, 0.025, 0.050, 0.075 and 0.100) spinel ferrites were prepared using sonochemical reactor. X-ray diffraction spectra were used to authorize/confirm the cubic spinel ferrite single-phase crystalline nature of the sample. The morphology of the prepared Ni0.5Cu0.25Zn0.25Fe2-xLaxO4 spinel ferrites was investigated by scanning electron microscope. It is observed that all the particles have devised spherical-like morphology. The ultrasonic non-destructive technique is also a versatile/flexible method/tool to explore/measure the Curie temperature (TC) in the spinel ferrites. In-situ ultrasonic velocity measurements in the range of temperature from 300 to 900 K were carried out. The detected anomalous characteristic/behavior in the ultrasonic velocity was used to explore the TC of the prepared sample. TC of Ni0.5Cu0.25Zn0.25Fe2-xLaxO4 is 735, 705,690, 675 and 655 K for the different composition x = 0.000, 0.025, 0.050, 0.075 and 0.100 respectively. The value of TC decreases with increasing La3+ doping concentration. Because La3+ ions are strongly paramagnetic, their presence reduces TC, which increases the paramagnetic zone. The vibrating sample magnetometry and susceptibility measurements have been used to investigate the influence of La3+ substitution on magnetic characteristics for further validation.

Discrimination of Poor Electrode Junctions within Lithium-Ion Batteries by Ultrasonic Measurement and Deep Learning

Lithium-ion batteries, which have high energy density, are the most suitable batteries for use in high-tech electromechanical applications requiring high performance. Because one of the important components that determines the efficiency of lithium-ion batteries is the electrode, the manufacturing process for this junction plays an important role in the entire production process. In particular, the process related to the resistance spot welding of the electrode is very important, directly affecting the safety of users, and greatly affecting the performance of the batteries. However, because the electrode tab is spot-welded onto the inner surface of the case, it is impossible to verify with visual testing (using the naked eye) whether the junction is well bonded. Therefore, it is very important to perform quality evaluation of the resistance welding of electrodes after completing the manufacturing process, using non-destructive testing methods. In this paper, a non-destructive ultrasonic testing technique was applied to examine the quality of lithium-ion batteries in which the negative electrode tabs were welded to the inner surface of the cell cans. The status of resistance spot welding between the electrode and the can was verified using deep-learning techniques with the experimentally acquired ultrasonic signal database.

Towards pure: The single-phase bulk omega titanium and modulation on its elastic properties under biaxial strains

Single-phase ω-phase Ti with a considerable size of 3 mm × 3 mm × 4 mm and a Vickers hardness of 2.5 GPa is synthesized under high pressure and combined with a designed experimental curve at room temperature. The elastic properties of the α- and ω-phase Ti are ascertained using the non-destructive ultrasonic through-transmission technique. Based on the investigated Raman spectra and DSC, the inverse transition temperature of the metastable ω-phase and Raman spectra of the α- and ω-structures are also discussed. Modulations on the elastic and spectral properties of the two phases are simulated using first-principles calculations to systematically investigate the mechanical responses under biaxial strains.