Guided Wave Testing Research Articles

Detection of Cut-Out in Aluminum Plate Using Ultrasonic Guided Waves: A Finite Element Analysis

<div>Aluminum alloys serve a critical role in the aerospace industry, accounting for a significant amount of commercial aircraft weight. Despite the growing use of composite materials, aluminum remains important in airframe construction due to its lightweight, cost-effectiveness, and high strength potential. Structural integrity is critical in modern engineering, necessitating early diagnosis and localization of damage. To detect the flaws, cracks, and cut-out in the structures, structural health monitoring (SHM) systems are essential, with non-destructive testing (NDT) methodologies playing critical roles. Among these technologies, ultrasonic guided wave testing (UGWT) has gained popularity because of its capacity to propagate over long distances and detect subsurface faults. This article investigates the use of UGWs to identify cut-outs in aluminum plates. The numerical investigation has been carried out using commercially available finite element software Abaqus. The ultrasonic lamb waves are generated through the load. The results obtained in pristine and defected 2D aluminum plate has been compared with proper selection of actuation and sensing points. Further by changing the location of actuation and sensing points the shift of damage scattering components has been observed. After identification of reflected wave mode, the location of the cut-out can be predicted accurately.</div>

Numerical investigation of bandgap characteristics in integrated metallic metafilters for nonlinear guided wave applications

Guided waves propagating in nonlinear media, featuring second harmonic generation, represent a promising avenue for early-stage damage detection due to their high sensitivity and long-range propagation capabilities. However, nonlinear ultrasonic measurements are hindered by nonlinearities induced by the experimental system, necessitating careful calibrations that have restricted their application to laboratory settings. While several phononic crystal and metamaterial designs have been devised to enhance nonlinear-based ultrasonic testing, most are tailored for suppressing second harmonics within a frequency range of 100–300 kHz, primarily utilizing low-frequency excitation. In this paper, we propose a metallic ring-shaped metafilter designed to explore high-order bandgaps. To fully understand the bandgap characteristics, we begin by analyzing mode shapes, providing insights into the underlying wave mechanics. The efficacy of the designed filter is subsequently assessed through 3D time step elastodynamic simulations. In addition, this study underscores the significance of parameters such as the number of rings employed in the filter, signal duration, and bandgap width in optimizing its performance. Furthermore, the observed mode conversion phenomena from S0 to A0 guided wave modes underscore the filter’s capacity to influence guided wave propagation. The defect localization technique, based on the time difference of arrival of second-order wave modes, accurately predicts the defect location with an error margin of less than 0.2%. The present investigation showcases advancements in the sensitivity of nonlinear-based guided wave testing for characterizing microstructural changes, promising substantial potential for detecting incipient damage in practical structural health monitoring applications.

Machine learning supported ultrasonic testing for characterization of cracks in polyethylene pipes

This study aims to develop a machine learning supported ultrasonic guided wave testing (UGWT) for detection and characterization of cracks in polyethylene (PE) pipes used for natural gas distribution. Ultrasonic testing is conducted to investigate the wave-crack interaction and determine damping properties of PE pipes. Finite element models are further built with material properties fine-tuned by wave attenuation experiments combined with cross-correlation analysis between the simulated and experimental signals. A synthetic database is populated using sensed signals over a wide range of crack geometries from numerical simulations. Finally, support vector machine (SVM) models are developed with different feature selections for classification of crack geometry and the accuracy is evaluated using both simulated and experimental cases. The findings demonstrate the potential of locating the circumferential position of crack with the ring-focusing method and classifying crack geometry in PE pipes using SVM model with central frequency features.

Research on the algorithm for optimal selection of detection modes for rail crack detection

In the application of ultrasonic guided wave testing for rail crack detection, it is necessary to select a guided wave mode that is more sensitive to cracks as the detection mode. However, ultrasonic guided waves have multi-mode and dispersive characteristics. In order to extract mode information from complex signals, this paper proposes an optimal detection mode selection method based on the sensitivity of guided wave modes to cracks. This method is different from the traditional method of determining mode types by calculating the mode velocity through the arrival time of wave packets in the time domain signal. Based on the dispersion characteristics and mode features of guided wave modes, this paper establishes a crack sensitivity evaluation index. In a wide frequency band and among numerous modes, the guided wave modes suitable for detecting cracks in different regions of the full cross-section of rails are accurately selected. Experimental results show that the guided wave modes selected by the mode selection method proposed in this paper, based on the crack area energy and crack reflection intensity evaluation indexes, can accurately identify rail cracks, laying a foundation for the research on rail crack detection and localization methods.

Comprehensive Inspection Solution for Boiler Water Wall Tube Corrosion

A substantial number of domestic coal-fired boilers, most of which have been in operation for numerous years, are susceptible to corrosion and tube ruptures within their high-temperature environment, often resulting in unplanned shutdowns. Despite the annual planned maintenance shutdowns, which involve routine inspections of water wall and furnace tubes to detect potential corrosion and erosion, the current non-destructive testing methods are generally localized. This approach, particularly with the considerable height variation of the water wall tubes (ranging from approximately 10 to 25 meters), may overlook segments with severe corrosion during localized ultrasonic thickness gauging. Although the experience of inspection teams reduces the chance of defect oversight, the demand for a comprehensive and effective inspection technique remains a priority for boiler operators. This study utilizes the characteristic of guided waves to propagate over a certain distance along pipelines, initiating an exploration into a comprehensive inspection solution for water wall tubes. Finite element simulation results demonstrate the suitability of utilizing a 120 kHz frequency for shear horizontal mode (SH0) testing on the fire side of water wall tubes. This mode effectively screens for localized corrosion within a 3-meter range. In the field of on-site boiler inspection, electromagnetic coils are employed to generate guided waves within water wall tubes. The gathered signals from each electromagnetic guided wave testing (EMGWT) are consolidated into a distribution map, indicating suspicious signal locations. Pulse eddy current testing (PECT) is employed to identify potential issues with guided waves without requiring surface preparation. If PECT reveals anomalies, the affected surface is polished, and phased array ultrasonic testing (PAUT) is conducted to quantitatively measure the remaining wall thickness due to corrosion. The theoretical exploration and on-site inspection outcomes affirm the feasibility of this approach, aimed at enhancing operational safety for boiler water wall tubes and mitigating the risks of tube ruptures and leaks. This comprehensive inspection solution amalgamates three advanced detection technologies, each capitalizing on its unique inspection characteristics to facilitate corrosion screening, corrosion scanning, and wall thickness sizing. Through the integration of these technologies, the overall inspection strategy ensures the utmost level of reliability.

Preface

20th Anglo-French Physical Acoustics Conference (AFPAC 2023) FOREWORD After two successive postponements due to a well-known malicious virus, the twentieth AFPAC was organized in France in Fréjus at the Villa Clythia, from January 24 to 27, 2023. To celebrate this twentieth edition by something special to be remembered, a picnic on the beach followed by a magnificent walk in the Estérel massif were organized, in very favorable weather (as shown by the picture below).This year again, the bet was successful! During the five half-days of conferences, 33 oral presentations including four invited talks were given, on very varied themes, all in the area of physical acoustics.The four high quality invited talks concerned subjects as varied as “The cochlea seen as an active metamaterial” by Fabrice Lemoult, “Guided wave testing of pipelines” by Mike Lowe, “Miniature ultrasonic surgical devices for integration with surgical robots” by Margaret Lucas and “Ultrasound backscattering by aggregating red blood cells for hematopathology” by Émilie Franceschini. The number of questions at the end of each of the 33 presentations was only a reflection of their high quality, sparking interest and cross-disciplinary scientific discussions, entirely in line with what the AFAPC wishes to promote.The two Rocard 2022 prizes (prize of the Société Française d’Acoustique to distinguish promising young researchers after their PhD) were awarded to Xinxin Guo and Matthieu Malléjac during this edition.Alain Lhémery (CEA-LIST, France), Samuel Raetz (Le Mans Université, France), SFA / GAPSUS, Nader Saffari (UCL, UK), Theodosia Stratoudaki (University of Strathclyde, UK), IOP / PAG.

A technique for medium-range through-thickness focusing using Lamb waves

Medium-range guided wave testing is commonly employed for inspection of areas with restricted access. The technique usually works in pulse echo mode and at high frequency-thickness products, around 20 MHz ⋅ mm, offering good sensitivity and resolution. Defect sizing is based on the reflection amplitude of the received mode(s). However, the scattering of guided waves is complex, and the amplitude of the reflected modes does not provide sufficient information for defect sizing. This work aims to overcome this limitation using a focusing technique based on Lamb waves. Specifically, multiple Lamb wave modes are excited individually and superimposed to form a new mode with a desired through-thickness energy distribution. This way, energy is focused on a single point in the structure. Using weighting functions, the location of the focal point is swept across the thickness of the sample. The technique allows for accurate sizing of flaws, such as cracks and wall loss.

Development of plant integrity inspection on the API 5L X65 material under humid conditions: emerging fitness for service assessment approach

This work reports the development and corresponding monitoring of pipeline integrity inspection in the arid zone, which typically experiences external corrosion. The recent method poses the challenge which indaquate to synchronize the internal and external corrosion monitoring of API 5L X65 material trunklines and flowlines owing to imperfect types of inspection on the external progressive damage only. Red-clay soil, soil porosity, oxygen content, and moisture become critical parameters for controlling the corrosion of the above conditions. The combination of ultrasonic guided wave test, visual inspection, and design life calculation is implemented to address the above challenges. Based on the results, trunkline B (12-inch) is more severe than A (18-inch), with the shorter measured remaining thickness and remaining life of 4.35 mm and 1.9 years. External corrosion and visual inspection results show that sand threatens corrosion. The external corrosion product is evident at the 3 and 6 o’clock positions, corresponding to the exposure of the buried pipelines to moisture. The maximum metal loss in the trunk is 14.5 %, which confirms the environment of trunkline B. The internal corrosion has little effect on the integrity of the plant. Despite the three fluid phases inside the flowlines and trunklines, the measured corrosion rate on the coupon is relatively lower. The highest recorded corrosion rate is 0.443 mmpy, while the contribution to internal corrosion from the rest of the monitor well is insufficient. This research is designed to model the strategy to utilize instrumentation of Ultrasonic tests and human intervention in corrosion mitigation

Multiscale 1-DCNN for Damage Localization and Quantification Using Guided Waves With Novel Data Fusion Technique and New Self-Attention Module

This article proposes an innovative damage localization and size quantification method named as MSCNNSAM based on new multiscale convolutional neural network (MSCNN) and novel small-weighted zero-setting self-attentive module (SAM) in carbon fiber reinforced plastic structures. Firstly, an improved piecewise aggregate approximation algorithm (IPAA) is developed to compress the guided wave signal and extract a series of damage indexes (DI). Considering the different effects of the damage location on the different sensing paths, a new method of damage information targeting enhancement and multipath data fusion is proposed. Then, a novel MSCNN architecture is also proposed for the inherent multiscale characteristics of the guided wave signal, which takes the multipath fused data as input and uses regression and classification methods to directly predict the location and size of the damage. Finally, to further improve the performance of the MSCNN, a SAM is proposed to effectively avoid the influence of low-information channel features and improve the damage feature extraction capability of the network. The proposed method is evaluated through experiments on a guided wave testing platform. Experimental results and comprehensive comparison analysis with respect to the state-of-the-art damage localization and quantification methods have demonstrated the superiority of the proposed MSCNNSAM.

XAI for signal analysis of guided wave testing at pipe elbows

Guided wave testing can provide an efficient screening method for local wall thinning of piping owing to its long inspection range and its ability to inspect pipes with limited access. However, there is a problem in signal interpretation of guided wave testing. While the interpretation of echo signals in guided wave testing is relatively simple for straight pipes, it becomes much more difficult when inspected piping includes an elbow because wave propagation becomes more complicated. This study investigates a signal analysis method that utilizes deep learning to evaluate local wall-thinning at an elbow based on echo signals in guided wave testing using multiple frequencies. To this end, we considered the configuration of deep learning system to analyze echo signals in guided wave testing and utilized Shapley additive explanations (SHAP), one of the explainable AI (XAI) techniques, to provide reasoning for prediction results obtained by deep learning models.

유도파 모드분리 및 반사계수에 의한 배관 결함검출

유도파 모드분리 및 반사계수에 의한 배관 결함검출

Applications of Linear Scanning Magnetostrictive Transducers (MST) for Finding Hard-to-Detect Anomalies in Structural Components

Guided wave testing is now a widely accepted method for detection of structural damage in many different types of components, from pipelines to pressure vessels to tanks. Torsional wave modes (T modes) in pipes and shear horizontal (SH) mode guided waves in plates are good candidates for finding areas with generalized corrosion, due to the absence of fluid coupling effects and their lack of dispersion. However, from our field test experience, certain types of defects are difficult to detect with conventional T mode or SH mode guided wave probes. Gradual wall thinning is one such type of defect; another is crack-like defects in or close to welds or penetrations in the pipe. Recently, Southwest Research Institute (SwRI) has developed a new sensor configuration and scanning system that overcomes these limitations. We have recently developed a linear scanning magnetostrictive transducer (MsT) probe system, in which a FeCo strip wound with radio frequency (RF) coils is attached to the structure under test with shear wave couplant, and a moving permanent magnet driven by a motor is used to excite SH guided waves at predefined positions along this strip. The probe is designed to operate over a wide frequency range (20 – 500 kHz) and can be used to generate dispersive shear wave mode (SH1) in addition to the nondispersive SH0 mode. The use of different modes with the sensor at multiple positions allows detection of a range of defect types. In this paper, the performance of linear scanning MsTs is presented, including experimental evaluation of detection of gradual wall thinning patches of different depths and locations on a steel pipe and plate mockups. Another set of experiments evaluates detection of notches in seam welds. Indications from real-time B-scan and SAFT (synthetic aperture focusing technique) processing will be presented.

Characteristic Parameters of Magnetostrictive Guided Wave Testing for Fatigue Damage of Steel Strands.

Steel strands are widely used in structures such as bridge cables, and their integrity is critical to keeping these structures safe. A steel strand is under the working condition of an alternating load for a long time, and fatigue damage is unavoidable. It is necessary to find characteristic parameters for evaluating fatigue damage. In this study, nonlinear coefficients and attenuation coefficients were employed to evaluate fatigue damage based on magnetostrictive guided wave testing. Unlike pipe and steel wire structures, there is a phenomenon of a notch frequency when guided waves propagate in steel strands. The influence of the notch frequency on the nonlinear coefficient and attenuation coefficient is discussed. The relationship between the nonlinear coefficient, attenuation coefficient, and cyclic loading times was obtained through experiments. The amplitudes of the nonlinear coefficient and attenuation coefficient both increased with the increase in cyclic loading times. The experiments also showed the effectiveness of using these two characteristic parameters to evaluate fatigue damage.

Damage Quantification and Identification in Structural Joints through Ultrasonic Guided Wave-Based Features and an Inverse Bayesian Scheme.

In this paper, defect detection and identification in aluminium joints is investigated based on guided wave monitoring. Guided wave testing is first performed on the selected damage feature from experiments, namely, the scattering coefficient, to prove the feasibility of damage identification. A Bayesian framework based on the selected damage feature for damage identification of three-dimensional joints of arbitrary shape and finite size is then presented. This framework accounts for both modelling and experimental uncertainties. A hybrid wave and finite element approach (WFE) is adopted to predict the scattering coefficients numerically corresponding to different size defects in joints. Moreover, the proposed approach leverages a kriging surrogate model in combination with WFE to formulate a prediction equation that links scattering coefficients to defect size. This equation replaces WFE as the forward model in probabilistic inference, resulting in a significant enhancement in computational efficiency. Finally, numerical and experimental case studies are used to validate the damage identification scheme. An investigation into how the location of sensors can impact the identified results is provided as well.

Damage localization and robust diagnostics in guided-wave testing using multitask complex hierarchical sparse Bayesian learning

The inversion of guided-wave data for accurate damage localization is a challenging problem when using guided waves for nondestructive testing and robust diagnostics. It is especially important to detect incorrect damage localization without knowing the original damage. In this paper, a new damage localization and robust diagnostics method is proposed. A Multi-task Complex Hierarchical Sparse Bayesian learning (MuCHSBL) algorithm is presented to solve the inverse problem for damage localization based on the data measured from a small number of sensors. The multi-task model improves the efficacy of damage localization by utilizing the consistency of damage locations for tasks with different signal frequencies. A Sparse Bayesian learning algorithm is also introduced to utilize the spatial sparsity of the damage, since structural damage typically occurs at only a few localized areas. The quantified posterior uncertainty of the model parameters gives a sense of confidence in the damage localization results. Utilizing the different levels of uncertainty in the optimal and suboptimal inversion models, diagnostic tools are proposed to detect whether the inversion for damage localization is accurate, without knowing the original damage. Numerical and experimental studies are carried out to verify the effectiveness of the proposed method. It is demonstrated that the damage localization efficacy of multi-task model is much higher than that of single-task model; moreover, the accuracy of damage localization results can be diagnosed effectively by the posterior uncertainty quantification of the model parameters.

Defect Characterization Method for Bridge Cables Based on Topology of Dynamical Reconstruction of Magnetostrictive Guided Wave Testing Signals

Defect Characterization Method for Bridge Cables Based on Topology of Dynamical Reconstruction of Magnetostrictive Guided Wave Testing Signals

Microcrack inspection in a functionally graded plate structure using nonlinear guided waves

The nonlinear guided wave technique based on contact acoustic nonlinearity (CAN) has been considered one of the best approaches for characterizing microcracks or fatigue cracks in structures. Through various mode selections, nonlinear guided wave testing has higher sensitivity that is suitable for detecting micro-defects at a very early stage. However, in most of the previous studies, this technique has been implemented in homogeneous materials such as aluminium, steel and layered composites. In recent years, functionally graded material (FGM) has received a great deal of attention because of its exceptional mechanical properties. Monitoring and evaluating the microstructural changes of FGM are essential for safety. In this study, the nonlinear interaction of the guided waves with a microcrack in an FGM plate is investigated numerically. The results showed that the generation of higher harmonics provides a sensitive means for detecting microcracks in FGM plates. Besides, the dependence of relative nonlinear parameters on microcrack length, sensor location and crack locations is studied through comprehensive finite element simulations. The study reveals that the nonlinear ultrasonic technique can be used effectively to detect microcracks in FGM plate structures.

Single-mode Lamb wave excitation at high-frequency-thickness products using a conventional linear array transducer

Lamb wave excitation at high-frequency-thickness products offers a potential solution for high-resolution guided wave testing. The method is attractive for crack imaging and corrosion mapping, especially in hidden locations where direct access is limited. However, multiple modes may propagate, complicating signal interpretation, which is undesirable. In this work, a systematic approach is presented, in an effort to determine the influence of the key parameters related to single higher order Lamb wave mode excitation using a conventional linear array transducer. Specifically, a linear time delay law is used to enhance the targeted mode, while the array's length, pitch and apodisation profile remain to be optimally selected. First, an analytical solution is derived based on modal analysis. This provides a natural decomposition of the amplitude of a guided wave mode into the product of the response of a single element and the excitation spectrum. Then, a key observation is made, associating the excitation spectrum to the directivity function for bulk wave phased array steering. This allows the application of well-established phased array analysis tools to guided wave phased array excitation. In light of this fact, minimisation of the spectrum’s bandwidth, elimination of the grating lobes and derivation of an apodisation profile are performed, to enhance the purity of the targeted mode. Finally, experiments conducted on an aluminium plate verify the above theoretical results. The Full Matrix is acquired, and all signals are reconstructed synthetically.

Ultrasonic guided wave testing on pipeline corrosion detection using torsional T(0,1) guided waves

Ultrasonic guided wave testing (UGWT) is used in rapid screening to detect, locate and classify corrosion defects. This non-destructive testing technique can perform wide-range inspection from a single point, thus reducing the time and effort required for NDT. However, the mode conversion phenomena and the dispersive nature of the guided waves make corrosion detection difficult. Hence, the parametric studies on the response signals of a T (0, 1) wave from pipe defects were presented in this paper. Firstly, a mathematical model of 6-inch schedule 40 pipes was developed. The corrosion profile of various geometries was then constructed on the outer surface of the pipeline by varying the circumferential length and depth. The numerical study was performed to analyse the characteristics of the response signals when a torsional guided wave impinges on the corroded pipelines. A five-cycle Hanning tone-burst signal with a central frequency of 30k Hz was used throughout the study. The results demonstrated that mode conversion to a flexural mode F (1, m) occurs when the stimulated T (0, 1) strikes non-symmetric defects. Nonetheless, as the circumferential extent of the corrosion increased, the response signals tended to behave symmetrically, and there was less mode conversion detected. Thus, the presence of flexural mode F (1, m) can be used as the criteria to distinguish symmetric and asymmetric faults. In addition, the results demonstrated that the reflection coefficients increase monotonically with the defect's depth due to the increases in the estimated cross-sectional area loss (ECL). As a result, a more significant proportion of the transmission wave was reflected. These findings serve as guidelines for on-site inspections. With the known speed of guided wave propagation, it is possible to precisely forecast the position of faults.

The use of circumferential guided waves to monitor axial cracks in pipes

Guided wave testing is in routine use to detect corrosion, particularly in the oil and gas sector, but the detection of axial cracking is difficult using the axially propagating waves commonly used for corrosion detection. This paper presents a novel guided wave monitoring technique for the detection of axial cracking in piping. Circumferential SH0 waves, travelling around the circumference were used in a monitoring configuration to detect axial defects in a 6 inch schedule 80 steel pipe. Finite Element (FE) analysis showed that both the defect reflection and the decline in the transmitted SH0 wave can be used for defect detection. Baseline subtraction was utilised to produce residual signals that can be better analysed for small defect reflections. The Root-Mean-Square (RMS) of the residual signal after baseline subtraction was found to be the most satisfactory means of monitoring defect progression. An amplification effect was identified where the residual signal is compounded by continued interaction with the defect on each revolution of the incident wave. The FE predictions were validated by an experiment in which an Electrical Discharge Machining (EDM) notch was grown in four stages. Temperature compensation using Location Specific Temperature Compensation (LSTC) was applied to the experimental data, allowing residuals to be compared for a ∼10 °C temperature swing over a monitoring period of over 2 months. It was determined that a 10 mm long (∼23% of wavelength), 5 mm deep (∼45% of the wall thickness) defect at an axial offset from the line of the transducers of 1.5 wavelengths (65 mm) would be readily detectable with a very high Probability of Detection (POD) and virtually no chance of a false call. Therefore, this novel guided wave monitoring system for axial crack detection is likely to be attractive for applications in a range of industries for its sensitivity to axial cracking combined with large coverage from a single transducer location.