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In recent years, with the development of materials science, the joining technology is also constantly upgraded, ultrasonic testing technology can more accurately detect the defects or failures of new materials in the new joining process, which has extensive applications in the field of engineering joining, such as welding, mechanical joining, and adhesive bonding. This paper introduces the common non-destructive testing techniques, including magnetic particle testing, eddy current testing, penetration testing, radiographic testing, and ultrasonic testing. The main principles and devices of ultrasonic testing are introduced, including air-coupled ultrasonic testing, electromagnetic ultrasonic testing, laser ultrasonic testing, and so on. The current status of the application of ultrasonic testing in welded joints, riveted joints, bonded joints, and bolted joints is summarized and reviewed. Finally, the drawbacks of ultrasonic testing in this field are discussed, as well as prospective research directions.

Non-destructive testing (NDT) methods are critical for evaluating the structural integrity of and detecting defects in composite materials across industries such as aerospace and renewable energy. This review examines the recent trends and successful implementations of NDT approaches for composite materials, focusing on articles published between 2015 and 2025. A systematic literature review identified 120 relevant articles, highlighting techniques such as ultrasonic testing (UT), acoustic emission testing (AET), thermography (TR), radiographic testing (RT), eddy current testing (ECT), infrared thermography (IRT), X-ray computed tomography (XCT), and digital radiography testing (DRT). These methods effectively detect defects such as debonding, delamination, and voids in fiber-reinforced polymer (FRP) composites. The selection of NDT approaches depends on the material properties, defect types, and testing conditions. Although each technique has advantages and limitations, combining multiple NDT methods enhances the quality assessment of composite materials. This review provides insights into the capabilities and limitations of various NDT techniques and suggests future research directions for combining NDT methods to improve quality control in composite material manufacturing. Future trends include adopting multimodal NDT systems, integrating digital twin and Industry 4.0 technologies, utilizing embedded and wireless structural health monitoring, and applying artificial intelligence for automated defect interpretation. These advancements are promising for transforming NDT into an intelligent, predictive, and integrated quality assurance system.

Additive manufacturing (AM) is a rising technology bringing new opportunities for design and cost of manufacturing, compared to standard processes like casting and machining. Among the AM techniques, direct energy deposition (DED) processes are dedicated to manufacture functional metallic parts. Despite of their promising perspectives, the industrial implementation of DED processes is inhibited by the lack of structural health control. Consequently, non-destructive testing (NDT) techniques can be investigated to inspect DED-manufactured parts, in an online or offline manner. To date, most ultrasonic NDT applications to metallic AM concerned the selective laser melting process; existing studies tackling DED processes mainly compare various ultrasonic techniques and do not propose a comprehensive control method for such processes. Current researches in the GeM laboratory focus on a multi-sensor monitoring method dedicated to DED processes, with a structural health control loop included, in order to track defect formation during manufacturing. In this way, this paper aims to be a proof of concept and proposes a comprehensive control method that opens the way to in situ ultrasonic control for DED. In this paper, a control method using the phased array ultrasonic testing (PAUT) technique is particularly illustrated on wire-arc additive manufacturing (WAAM) components, and its applicability to laser metal deposition (LMD) is also demonstrated. A specific attention is given to the calibration method, towards a quantitative prediction of the size of the detected flaws. PAUT predictions are cross-checked thanks to X-ray radiography, which demonstrates that the PAUT method enables to detect and dimension defects from 0.6 to 1 mm for WAAM aluminum alloy parts. Then, an applicable scenario of inspection of a WAAM industrial and large-scale part is presented. Finally, perspectives for in situ and real-time application of the chosen method are given. This paper shows that real-time monitoring of the WAAM process is possible, as the PAUT method can be integrated in the manufacturing environment, provides relevant in situ data, and runs with computing times compatible with real-time applications.

This paper presents an ultrasonic inspection methodology to improve the fitness-for-service (F.F.S) assessment of hydraulic turbine runners after manufacturing or during the in-service inspection. The improvement proposed here is to apply ultrasonic array inspection techniques with an emphasis on the total focusing method (TFM) to produce data compatible with fitness-for-service methodologies. Conventional ultrasonic inspection methods based on good workmanship are mandatory for manufacturing, and in-service inspections are generally limited to surface methods such as penetrant or magnetic testing. Our previous work found serious limitations with conventional ultrasonic testing (UT) applied to the high-stress area located in the welded joint between the blade and the band. Undetected flaws will likely remain in a weld after fabrication, which can reduce the component’s service life. Our work is centered on a real turbine runner using various ultrasonic array configurations to characterize detected flaws left after fabrication. According to an evaluation of a Francis turbine runner, our results suggest that a dedicated TFM transducer with passive axis focusing and encoded inspection results in a higher detection rate, more accurate flaw definition, and more accurate sizing for the fitness-for-service (F.F.S) assessment of hydraulic turbine runners.

Aluminum–Magnesium (Al–Mg) alloys undergo sensitization, i.e., the precipitations of β-phase (Al2Mg3) at the grain boundaries, when exposed to elevated temperature. This microstructural change increases the susceptibility of Al–Mg alloys to intergranular corrosion, exfoliation, and stress corrosion cracking. This study introduces a time-frequency analysis (TFA) technique to determine the frequency-dependent ultrasonic attenuation parameter and correlate the frequency-attenuation slope to the Degree of Sensitization (DoS) developed in heat-treated Al–Mg alloy samples. Broadband pitch-catch signal was generated using a laser ultrasonic testing (LUT) system, from which the narrowband pitch-catch signal at different frequencies can be digitally generated. The attenuation parameters of sensitized Al–Mg samples were determined from these narrowband pitch-catch signals using the primary pulse-first echo (PP-FE) method. By identifying the frequency range within which the attenuation parameter is linearly proportional to the frequency, the slopes of the frequency-attenuation relationship were determined and correlated with the DoS values of the sample plates. The experimental results validate that the frequency-attenuation slope has a higher sensitivity and lower scattering as compared to other conventional ultrasonic attenuation measurement techniques.

New construction or existing structures are tested for material quality as well as damage and defects during their life cycle. Advancements in data science and sensor technologies have significantly improved Non-Destructive Testing (NDT) for monitoring the health of civil structures. This review covers 82 recent studies on ultrasonic testing (UT) methods used in civil NDT/E. It explains basic ultrasound principles, new developments in signal and image processing, and evaluates key imaging techniques like Synthetic Aperture Focusing Technique (SAFT), Total Focusing Method (TFM), and Computed Tomography (CT) for identifying defects and assessing materials. The review also discusses the use of advanced signal processing methods to better characterize defects and enhance image quality. Emerging trends include the use of machine learning for automatically identifying defects, new sensor technologies for real-time monitoring, and integrated monitoring systems using Internet of Things (IoT) and edge computing. Applications in material evaluation and testing structural components such as bridges and buildings are also examined. The review highlights challenges like handling large amounts of data, ensuring efficient computations, and creating standardized testing protocols. Future research directions aim to make UT methods more accurate, reliable, and scalable, contributing to the safety and durability of civil infrastructure. This review provides valuable information for researchers, engineers, and industry professionals on the latest developments, current challenges, and future opportunities in ultrasonic-based civil infrastructure NDT/E.

Additively manufactured components are gaining popularity in aerospace, automotive and medical engineering applications. Additive manufacturing (AM) offers tremendous cost advantages over traditional manufacturing methods. However, inter- and intra-layer defects are observed in AM components. Moreover, the lack of appropriate testing methods for assessing the integrity of AM components deters its use, despite the several functional advantages it has to offer. Non-destructive testing (NDT) forms the most common and convenient way of inspecting parts. In this paper, a laser ultrasonic technique for the inspection of AM components is proposed. The results demonstrate laser ultrasonic testing (LUT) as a promising method for the non-contact inspection of additive manufactured components. Furthermore, the results were validated using X-ray computed tomography (CT) and ultrasonic immersion testing (UIT). The sample used in this study was manufactured through selective laser melting (SLM) AM process with built-in holes representing defects.

Honeycomb sandwich composite panels have complex structures, large sizes, many types of defects, and significant sound attenuation, which lead to low efficiency and poor sensitivity of ultrasonic non-destructive testing. In the study, a non-linear ultrasonic lamb wave testing technique for honeycomb sandwich composite panels is proposed. Firstly, the anisotropic propagation characteristics and modal structure of lamb waves in honeycomb sandwich composite panels are analyzed, and the lamb wave modes with non-linear ultrasonic accumulation are excited. Secondly, the data extraction method and imaging algorithm of non-linear ultrasonic lamb wave imaging testing are proposed. Finally, an enhanced imaging algorithm is proposed to improve image quality based on the sliding window algorithm. Based on the comparative analysis of air-coupled ultrasonic testing images and metallographic tests, it can be seen that non-linear ultrasonic lamb wave testing signals can be used to characterize the damage distribution characteristics of honeycomb sandwich composite panels, display debonding and weak debonding defects, and have the advantages of being able to perform on the same side testing and high efficiency, which can be used for non-destructive testing of honeycomb sandwich composite panels.

The ultrasonic test is a promising non-destructive testing technique for evaluating the properties of asphalt mixtures. To investigate the applicability and reliability of ultrasonic testing technology (UTT) in evaluating the performance of asphalt mixtures, ultrasonic tests, indirect tensile tests, compression tests, and dynamic modulus tests were carried out at various temperatures. Subsequently, the distribution characteristics of ultrasonic traveling parameters for asphalt mixtures were analyzed. The variation of ultrasonic pulse velocity and amplitude in dry and wet states with temperature was studied. Then, the correlation between the ultrasonic parameters and both the volume parameters and the mechanical performance parameters of asphalt mixtures was revealed, and the functional relationship between ultrasonic pulse velocity and compressive strength was established. Finally, the reliability of predicting high-frequency dynamic modulus by ultrasonic velocity was verified. The laboratory tests and analysis results indicate that both ultrasonic pulse velocity and amplitude in dry and wet conditions show a decreasing trend with an increase in temperature. Ultrasonic parameters are greatly influenced by asphalt content and mineral aggregate content of 9.5~13.2 mm and 13.2~16 mm. The dynamic modulus at a high-frequency load can be predicted by using ultrasonic velocity, and predicting the results for OGFC and SMA mixtures deduced by using the UPV at a high-frequency load have higher reliability.

Combinative methodologies have the potential to address the drawbacks of unimodal non-destructive testing and evaluation (NDT & E) when inspecting multilayer structures. The aim of this study is to investigate the integration of information gathered via phased-array ultrasonic testing (PAUT) and pulsed thermography (PT), addressing the challenges posed by surface-level anomalies in PAUT and the limited deep penetration in PT. A center-of-mass-based registration method was proposed to align shapeless inspection results in consecutive insertions. Subsequently, the aligned inspection images were merged using complementary techniques, including maximum, weighted-averaging, depth-driven combination (DDC), and wavelet decomposition. The results indicated that although individual inspections may have lower mean absolute error (MAE) ratings than fused images, the use of complementary fusion improved defect identification in the total number of detections across numerous layers of the structure. Detection errors are analyzed, and a tendency to overestimate defect sizes is revealed with individual inspection methods. This study concludes that complementary fusion provides a more comprehensive understanding of overall defect detection throughout the thickness, highlighting the importance of leveraging multiple modalities for improved inspection outcomes in structural analysis.