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Ice detection poses significant challenges in sectors such as renewable energy and aviation due to its adverse effects on aircraft performance and wind energy production. Ice buildup alters the surface characteristics of aircraft wings or wind turbine blades, inducing airflow separation and diminishing the aerodynamic properties of these structures. While various approaches have been proposed to address icing effects, including chemical solutions, pneumatic systems, and heating systems, these solutions are often costly and limited in scope. To enhance the cost-effectiveness of ice protection systems, reliable information about current icing conditions, particularly in the early stages, is crucial. Ultrasonic guided waves offer a promising solution for ice detection, enabling integration into critical structures and providing coverage over larger areas. However, existing techniques primarily focus on detecting thick ice layers, leaving a gap in early-stage detection. This paper proposes an approach based on high-order symmetric modes to detect thin ice formation with thicknesses up to a few hundred microns. The method involves measuring the group velocity of the S1 mode at different temperatures and correlating velocity changes with ice layer formation. Experimental verification of the proposed approach was conducted using a novel group velocity dispersion curve reconstruction method, allowing for the tracking of propagating modes in the structure. Copper samples without and with special superhydrophobic multiscale coatings designed to prevent ice formation were employed for the experiments. The results demonstrated successful detection of ice formation and enabled differentiation between the coated and uncoated cases. Therefore, the proposed approach can be effectively used for early-stage monitoring of ice growth and evaluating the performance of anti-icing coatings, offering promising advancements in ice detection and prevention for critical applications.
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Multilayer printed circuit boards (PCBs) can be produced not only in the traditional way but also additively. Both traditional and additive manufacturing can lead to invisible defects in the internal structure of the electronic component, eventually leading to the spontaneous failure of the device. No matter what kind of technology is used for the production of PCBs, when they are used in important structures, quality control is important to ensure the reliability of the component. The nondestructive testing (NDT) of the structure of manufactured electronic components can help ensure the quality of devices. Investigations of possible changes in the structure of the product can help identify the causes of defects. Different types of manufacturing technologies can lead to diverse types of possible defects. Therefore, employing several nondestructive inspection techniques could be preferable for the inspection of electronic components. In this article, we present a comparison of various NDT techniques for the evaluation of the quality of PCBs produced using traditional and additive manufacturing technologies. The methodology for investigating the internal structure of PCBs is based on several of the most reliable and widely used technologies, namely, acoustic microscopy, active thermography, and radiography. All of the technologies investigated have their advantages and disadvantages, so if high-reliability products are to be produced, it would be advantageous to carry out tests using multiple technologies in order to detect the various types of defects and determine their parameters.
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In guided-wave-based damage-imaging algorithms, damage reconstruction typically involves comparing the signals with and without a defect. However, in many cases, defect-free data may not be available. Therefore, in this study, baseline and baseline-free approaches were used for damage imaging, exploiting not only the amplitude of the signal as the feature but also five additional features, namely, the amplitude of the sparse signal after deconvolution, the amplitude of the coefficients at the excitation frequency from the re-assigned short-time Fourier transform, the time of flight determined from cross-correlation, kurtosis in the time domain, and kurtosis in the frequency domain. For this study, three different plates with different types of defects were considered: a metallic plate with a notch-type artificial defect, a pultruded type of composite plate with an impact defect, and a laminate composite plate with plexiglass serving as an added mass damper artificial defect. The Reconstruction Algorithm for Probabilistic Inspection of Damage (the RAPID algorithm) was used to characterize the defects on the three plates, and the defect parameters were then quantified by creating an ellipse after thresholding.
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This research utilizes Ultrasonic Guided Waves (UGW) to inspect corrosion-type defects in steel pipe walls, providing a solution for hard-to-reach areas typically inaccessible by traditional non-destructive testing (NDT) methods. Fundamental helical UGW modes are used, allowing the detection of defects anywhere on the pipe's circumference using a limited number of transducers and measurements on the upper side of the pipe. Finite element (FE) modeling and experiments investigated generating and receiving UGW helical waves and their propagation through varying corrosion-type defects. Defect detection is based on phase delay differences in the helical wave's signal amplitude peaks between defective and defect-free regions. Phase delay variations were noted for the different depths and spatial dimensions of the defects. These results highlight the phase delay method's potential for NDT pipeline inspection.
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Pipeline structures are susceptible to corrosion, leading to significant safety, environmental, and economic implications. Existing long range guided wave inspection systems often fail to detect footprints of the concentrated defects, which can lead to leakage. One way to tackle this issue is the utilization of circumferential guided waves that inspect the pipe's cross section. However, achieving the necessary detection resolution typically necessitates the use of high-order modes hindering the inspection data interpretation. This study presents the implementation of an ultrasonic technique capable of detecting and classifying wall thinning and concentrated defects using high-order guided wave modes. The technique is based on a proposed phase velocity mapping approach, which generates a set of isolated wave modes within a specified phase velocity range. By referencing phase velocity maps obtained from defect-free stages of the pipe, it becomes possible to observe changes resulting from the presence of defects and assign those changes to the specific type of damage using artificial neural networks (ANN). The paper outlines the fundamental principles of the proposed phase velocity mapping technique and the ANN models employed for classification tasks that use synthetic data as an input. The presented results are meticulously verified using samples with artificial defects and appropriate numerical models. Through numerical modeling, experimental verification, and analysis using ANN, the proposed method demonstrates promising outcomes in defect detection and classification, providing a more comprehensive assessment of wall thinning and concentrated defects. The model achieved an average prediction accuracy of 92% for localized defects, 99% for defect-free cases, and 98% for uniform defects.
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The article is devoted to the investigation of ultrasonic inspection techniques suitable for detecting hydrogen-induced cracking (HIC) and a high-temperature hydrogen attack (HTHA), which are of great importance in petrochemical and refinery industries. Four techniques were investigated: total focusing method (TFM), advanced velocity ratio (AVR) measurement, advanced ultrasonic backscatter technique (AUBT) and time of flight diffraction method using ultra low angle ultrasonic transducers (TULA). The experimental investigation has been carried out on two carbon steel samples cut off from a heat exchanger of an oil refinery and potentially affected by HIC. It was shown that the AVR technique did not reveal any damage and was not effective in the case of the investigated samples due to a thin damage zone with respect to the total thickness of the samples. The AUBT method enabled us to indicate and classify the presence of the hydrogen-induced damage; however, it is complicated to use in practise due to the need perform measurements exactly at the same position using two transducers of different frequencies. The method is more suitable for the verification of damage at a particular position, rather than for scanning. Both other methods-TFM and TULA-enabled us to identify the presence of HIC in large areas of samples. The obtained results have been verified using a metallographic analysis of the section cut from the side of the sample. The results of metallographic examinations have been compared with indications observed using above mentioned techniques and a good correspondence was obtained. It was demonstrated, that the TFM method can detect cracks with dimensions close to 200 µm, while larger cracks of 2 mm were observed very evidently using a 7.5 MHz phased array. Overall, the results suggested that the TULA method is the most suitable method for the primary detection of hydrogen-induced cracking, while the TFM is recommended for the precise assessment of the extent of the detected cracking.
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Fibre-reinforced composite laminates are frequently used in various engineering structures, due to their increased weight-to-stiffness ratio, which allows to fulfil certain regulations of CO2 emissions. Limited inter-laminar strength makes composites prone to formation of various defects, which leads to progressive degradation of residual strength and fatigue life of the structure. Using ultrasonic guided waves is a common technique for assessing the structural integrity of composite laminates. Phase velocity is one of the fundamental characteristics of guided waves and can be used for defect detection, material property estimation, and evaluation of dispersion. In this paper, a phase velocity reconstruction approach, based on the phase-shift method, was proposed, which uses frequency sweep excitation to estimate velocity at specific frequency harmonics. In contrast to the conventional phase spectrum technique, the proposed approach is applicable to the narrowband piezoelectric transducers and suitable for the reconstruction of dispersion curves for direct, converted, and multiple co-existing modes with high accuracy. The proposed technique was validated with finite element simulations and experiments, both on isotropic and anisotropic structures, analysing the direct, converted, and overlapped modes. The results demonstrated that, using the proposed technique, the phase velocity dispersion can be reconstructed at -20 dB level bandwidth of the transducer, with a relative error of ±4%, compared to the theoretical velocity predictions.
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Industrial inspection protocols are qualified using mock-ups manufactured according to the same procedure as the plant part. For coarse-grained castings, known for their low inspectability, relying on mock-ups becomes particularly challenging owing to the variability of grain properties among components. Consequently, there is a keen interest in the capability to verify whether the grain size of the component under test matches the qualification specification in-situ. This paper investigates the potential of an attenuation measurement for assessing the ultrasonic inspectability of coarse-grained components using qualified procedures in a practical setting. The experimental part of the study focuses on an industrial Inconel 600 mock-up with spatially varying attenuation, measured across the entire sample in an immersion tank. Three zones with distinctly different attenuations were examined using metallography, which allowed for calculating classical grain size histograms and two-point correlation functions. For one of the zones, we synthesised the microstructure with the same statistical properties numerically and simulated the propagation of ultrasound using a grain-scale finite element model. The results showed good agreement with the experiment, and lead to several suggestions for the reasons for the discrepancy, the varying grain size statistics being the most likely. A parametric study, which followed, depicted the effect of the mean and standard deviation-to-mean ratio of the log-normal grain size distribution on the attenuation of ultrasound and its frequency dependence. Most notably, we demonstrated the known non-uniqueness of the relationship between the log-normal grain size distribution parameters and the attenuation. We suggested that the correlation length calculated from a single exponential fit to the two-point correlation function is a more robust metric describing grain statistics for this context, which can be obtained from attenuation. The correlation lengths estimated from measured attenuation using the second-order approximation model for the three zones of the studied mock-up yielded results of acceptable accuracy. We concluded that this metric could replace the average grain size in practical settings, as it retains more statistical information than the mean grain size and allows for linking measurements to the established theoretical attenuation models which this paper demonstrates.
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According to the statistics, 40% of unplanned disruptions in electricity distribution grids are caused by failure of equipment in high voltage (HV) transformer substations. These damages in most cases are caused by partial discharge (PD) phenomenon which progressively leads to false operation of equipment. The detection and localization of PD at early stage can significantly reduce repair and maintenance expenses of HV assets. In this paper, a non-invasive PD detection and localization solution has been proposed, which uses three ultrasonic sensors arranged in an L shape to detect, identify and localize PD source. The solution uses a fusion of ultrasonic signal processing, machine learning (ML) and deep learning (DL) methods to classify and process PD signals. The research revealed that the support vector machines classifier performed best among two other classifiers in terms of sensitivity and specificity while classifying discharge and surrounding noise signals. The proposed ultrasonic signal processing methods based on binaural principles allowed us to achieve an experimental lateral source positioning error of 0.1 m by using 0.2 m spacing between L shaped sensors. Finally, an approach based on DL was suggested, which allowed us to detect a single PD source in optical images and, in such a way, to provide visual representation of PD location.
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BACKGROUND The aim of this study was to evaluate the ability of different rotary glide path techniques to maintain canal anatomy by comparing canal transportation and centring abilities in curved root canals using X-ray micro-computed tomography (micro-CT). MATERIAL AND METHODS We selected 36 root canals and randomly assigned them to 3 groups. The first group was instrumented using Pathfile (PF) 1 and PF2, the second group using PF2, and the third group using a Proglider (PG) instrument. Selected tooth samples were scanned using a micro-CT system with 8-µm resolution. Centring ability and transportation were compared at 5 levels: 0.5 mm (A0) and 1 mm (A1) from apical foramen, at the point of maximum root curvature (C0), at 1 mm below it (C-), and 1 mm above it (C+). Area, ratio of areas (RA), perimeter, centroid shift, mean diameter, and ratio of diameter ratios (RDR) were assessed. RESULTS In all groups, there were no significant differences between different levels in all parameters (p>0.05). In group 1, the centroid shift was greatest at A0 and C-, and the least impact was at C0. In group 2, the biggest impacts were at C- and A0, and the smallest at C+. In group 3, the greatest impacts were at A0 and A1, and the smallest at C0. CONCLUSIONS All 3 instrument groups performed very similarly, without significant differences in canal-shaping parameters. Overall, using just PF2 instead of PF 1 and 2 created very similar shaping results, which could reduce the number of instruments needed and the cost of treatment.
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Preparación del Conducto Radicular/instrumentación , Preparación del Conducto Radicular/métodos , Tratamiento del Conducto Radicular/métodos , Cavidad Pulpar/cirugía , Diseño de Equipo , Humanos , Diente Molar , Ápice del Diente , Microtomografía por Rayos X/métodosRESUMEN
Ultrasonic inspection is widely used for non-destructive evaluation of composite adhesive joints. However, there are serious challenges in applying ultrasonic testing on metal to composite hybrid joints, because they are multi-layered, made out of dissimilar materials and relatively thin. The ultrasonic signals reflected by different layers are overlapped, scattered and attenuated. The aim of this research was to develop an ultrasonic inspection technique suitable for defect detection in hybrid metal to composite joints where the metal part has pin arrays, which entangle with the composite part. The immersion pulse echo technique was used to collect data. In order to overcome the problems related to the rough surface and non-parallel layers a novel signal post-processing algorithm for reconstruction of the joint area was developed and validated experimentally. It is shown that using the proposed technique the positions of different defects can be determined.
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In this paper, a novel 2D analytical model based on the Huygens's principle of wave propagation is proposed in order to predict the directivity patterns of contact type ultrasonic transducers in the generation of guided waves (GWs). The developed model is able to estimate the directivity patterns at any distance, at any excitation frequency and for any configuration and shape of the transducers with prior information of phase dispersive characteristics of the guided wave modes and the behavior of transducer. This, in turn, facilitates to choose the appropriate transducer or arrays of transducers, suitable guided wave modes and excitation frequency for the nondestructive testing (NDT) and structural health monitoring (SHM) applications. The model is demonstrated for P1-type macro-fiber composite (MFC) transducer glued on a 2 mm thick aluminum (Al) alloy plate. The directivity patterns of MFC transducer in the generation of fundamental guided Lamb modes (the S0 and A0) and shear horizontal mode (the SH0) are successfully obtained at 80 kHz, 5-period excitation signal. The results are verified using 3D finite element (FE) modelling and experimental investigation. The results obtained using the proposed model shows the good agreement with those obtained using numerical simulations and experimental analysis. The calculation time using the analytical model was significantly shorter as compared to the time spent in experimental analysis and FE numerical modelling.
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This work proposes a novel hybrid signal processing technique to extract information on disbond-type defects from a single B-scan in the process of non-destructive testing (NDT) of glass fiber reinforced plastic (GFRP) material using ultrasonic guided waves (GW). The selected GFRP sample has been a segment of wind turbine blade, which possessed an aerodynamic shape. Two disbond type defects having diameters of 15 mm and 25 mm were artificially constructed on its trailing edge. The experiment has been performed using the low-frequency ultrasonic system developed at the Ultrasound Institute of Kaunas University of Technology and only one side of the sample was accessed. A special configuration of the transmitting and receiving transducers fixed on a movable panel with a separation distance of 50 mm was proposed for recording the ultrasonic guided wave signals at each one-millimeter step along the scanning distance up to 500 mm. Finally, the hybrid signal processing technique comprising the valuable features of the three most promising signal processing techniques: cross-correlation, wavelet transform, and Hilbert-Huang transform has been applied to the received signals for the extraction of defects information from a single B-scan image. The wavelet transform and cross-correlation techniques have been combined in order to extract the approximated size and location of the defects and measurements of time delays. Thereafter, Hilbert-Huang transform has been applied to the wavelet transformed signal to compare the variation of instantaneous frequencies and instantaneous amplitudes of the defect-free and defective signals.
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Ultrasonic guided wave (UGW)-based condition monitoring has shown great promise in detecting, localizing, and characterizing damage in complex systems. However, the application of guided waves for damage detection is challenging due to the existence of multiple modes and dispersion. This results in distorted wave packets with limited resolution and the interference of multiple reflected modes. To develop reliable inspection systems, either the transducers have to be optimized to generate a desired single mode of guided waves with known dispersive properties, or the frequency responses of all modes present in the structure must be known to predict wave interaction. Currently, there is a lack of methods to predict the response spectrum of guided wave modes, especially in cases when multiple modes are being excited simultaneously. Such methods are of vital importance for further understanding wave propagation within the structures as well as wave-damage interaction. In this study, a novel method to predict the response spectrum of guided wave modes was proposed based on Fourier analysis of the particle velocity distribution on the excitation area. The method proposed in this study estimates an excitability function based on the spatial dimensions of the transducer, type of vibration, and dispersive properties of the medium. As a result, the response amplitude as a function of frequency for each guided wave mode present in the structure can be separately obtained. The method was validated with numerical simulations on the aluminum and glass fiber composite samples. The key findings showed that it can be applied to estimate the response spectrum of a guided wave mode on any type of material (either isotropic structures, or multi layered anisotropic composites) and under any type of excitation if the phase velocity dispersion curve and the particle velocity distribution of the wave source was known initially. Thus, the proposed method may be a beneficial tool to explain and predict the response spectrum of guided waves throughout the development of any structural health monitoring system.
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Multi-wire ropes are widely used as load-carrying constructional elements in bridges, cranes, elevators, etc. Structural integrity of such ropes can be inspected by using non-destructive ultrasonic techniques. The objective of this work was to investigate propagation of ultrasonic guided waves (UGW) along composite multi-wire ropes in the cases of various types of acoustic contacts between neighboring wires and the plastic core. The modes of UGW propagating along the multi-wire ropes were identified using modelling, the dispersion curves were calculated using analytical and semi-analytical finite element (SAFE) techniques. In order to investigate the effects of UGW propagation, the two types of the acoustic contact between neighboring wires were simulated using the 3D finite element method (FE) as well. The key question of investigation was estimation of the actual boundary conditions between neighboring wires (solid or slip) and the real depth of penetration of UGW into the overall cross-section of the rope. Therefore, in order to verify the results of FE modelling, the guided wave penetration into strands of multi-wire rope was investigated experimentally. The performed modelling and experimental investigation enabled us to select optimal parameters of UGW to be used for non-destructive testing.