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Any subsurface anomaly present in asphalt pavement layers may lead to their localised progressive structural failure. The detrimental effects of such anomalies are not visible on the top surface in the early stages. It may cause a major cost escalation if gone unnoticed during construction or maintenance works. Hence, there is a need for their quick and reliable detection and assessment. Present study explores the non-destructive assessment of subsurface anomalies (such as void/buried utility, etc.) in asphalt layers. This work developed a simple experimental approach using the two-receiver Spectral Analysis of Surface Waves (SASW) method to generate the experimental dispersion curves (EDC) whose shape characteristics are utilised for the detection, location, and identification of subsurface anomalies. An in-situ asphalt pavement test-pit facility was developed consisting of a number of different sub-sections with various anomaly conditions. A test system utilising high-frequency accelerometers was custom-integrated for such assessments. Based on the EDC shape characteristics, a direct information extraction technique was developed which does not require backcalculation procedures. The study found the proposed technique to be reasonably applicable for a quick, non-destructive detection and assessment of the subsurface anomalies. Further extensive testing with different profiles, anomalies, and test conditions will help in further acceptance of this simple approach. [ABSTRACT FROM AUTHOR]

In this article, an image processing-based localization system is developed for remote nondestructive evaluation of welds within industrial assets. Manual ultrasonic inspection of large-scale structures is often repetitive, time-consuming, and benefits greatly from robotic support, however, these robotic systems are often fixed to a single purpose, lack self-awareness of their surrounding environment, and can be limited to simple geometry. For the inspection of welds, which are often carried out using phased array ultrasonic testing, there is a reliance on the use of surface features for automated tracking such as the laser profiling of a weld cap. For the inspection of more complex geometry such as nonlinear or saddle welds, a more positionally sensitive method is required. The proposed system utilizes information already available to a nondestructive inspector in the form of live phased array ultrasonic images to estimate the location of the weld using nonsurface, volumetric data. Data is captured using a 64-element, 10-MHz phased array probe mounted to the end effector of a small robotic manipulator which increases the scope of applications due to its heightened flexibility when compared to on-the-market alternatives. Morphological operations are applied to the ultrasonic data to reduce the noise apparent from regions of parent material and promote the data reflected from grain boundaries within the weld material. Through a series of image processing techniques, it is possible to predict the position of a weld under inspection with an absolute mean positional error of $\mathrm {0.8 \text {m} \text { m} }$ . From this study, the localization system is to be embedded within a remote system for extensive data acquisition of welds on large structures.

Machine learning plays an increasingly important role in the non-destructive testing and evaluation of composites. Principal component thermography (PCT) is often used as a popular feature extraction and dimension reduction method of thermographic data. However, the ability of PCT to handle large-scale thermographic data affects the applicability of PCT for high-resolution thermographic NDT. In this paper, fast randomized sparse principal component thermography (FRSPCT) is used to detect subsurface defects of glass fiber reinforced polymer (GFRP) composites. The effectiveness of the method is demonstrated by large-scale thermographic data of GFRP with subsurface defects. Furthermore, a comprehensive quantitative comparison of the method and other state-of-the-art methods was also conducted with respect to the signal-to-noise ratio, detection rate, and runtime. The comparison results show that the FRSPCT method gives the overall highest signal-to-noise ratio, detection rate, and satisfactory runtime. In addition, the method provides more easily interpretable defect detection results and highlights the hidden details of irregularly-shaped abnormal defects. [ABSTRACT FROM AUTHOR]

The Synthetic Aperture Focusing Technique (SAFT) is employed in laser ultrasonic non-destructive testing to image defects. However, during the laser ultrasonic imaging process, the influence of multi-mode waves often introduces various artifacts in the imaging results. We investigated a multi-iteration frequency-domain SAFT (MIF-SAFT) algorithm to tackle this challenge. Initially, a single low-precision F-SAFT imaging result is performed to identify potential defect locations. Subsequently, a back-projection method is applied to determine defect positions and separates acoustic waves of different modes in the B-scan. After that, a multi-mode F-SAFT imaging is performed for evaluation, and the above process is repeated until the imaging outcome stabilizes. The result shows that artifacts are removed when the image remains unchanged after multiple iterations, and the imaging quality is effectively improved by MIF-SAFT. Furthermore, including directivity patterns of laser ultrasound also enhances defect imaging capabilities within MIF-SAFT. Additionally, we examined the MIF-SAFT's capacity to detect multiple defects, which can image them simultaneously. • Multi-iteration in F-SAFT for artifact removal. • Different ultrasonic signals are separated by using the algorithm. • Directivity patterns are performed to enhance the imaging result. • Applied for multiple defects imaging simultaneously. [ABSTRACT FROM AUTHOR]

An innovative friction stir processing variant, named Upward Friction Stir Processing (UFSP), for producing customized materials with multifunctional particles is presented. In the UFSP, an upward flow is used to disperse these functional particles in a metallic matrix, in opposition to the widely used downward flow. As a proof of concept, SiC particles were introduced and dispersed into an aluminum alloy AA7075-T651 matrix to study different process parameters and to validate this novel material processing technology. Six different small-sized ingots were produced and compared to the conventional FSP technology. The microstructural evolution is studied by means of light microscopy, eddy current testing, microhardness mapping and advanced characterization techniques, such as high-energy synchrotron X-ray diffraction, scanning electron microscopy, energy-dispersive X-ray spectroscopy and electron backscatter diffraction. The number of passes was seen to greatly impact the particle distribution. Additionally, UFSP promotes a more uniform particle distribution over a larger processed area, when the lateral tool offset progress along the retreating side. [ABSTRACT FROM AUTHOR]

Abstract Cracks, especially small cracks are difficult to be detected in oil and gas transportation pipelines buried underground or covered with layers of material by using the traditional ultrasonic inspection techniques. Therefore, a new composite ultrasonic transducer array with three acoustic beam incidence modes is developed. The space model of the array is also established to obtain the defect reflection point location. And the crack ultrasound image is thus formed through a series of small cubical elements expanded around the point locations by using the projection of binarization values extracted from the received ultrasonic echo signals. Laboratory experiments are performed on a pipeline sample with different types of cracks to verify the effectiveness and performance of the proposed technique. From the image, the presence of small cracks can be clearly observed, in addition to the sizes and orientations of the cracks. The proposed technique can not only inspect common flaws, but also detect cracks with various orientations, which is helpful for defect evaluation in pipeline testing.

Non-destructive testing and evaluation (NDT&E) plays a vital role in industrial quality control and structural health monitoring. Among various NDT&E approaches, infrared thermography plays a crucial role due to its merits such as fast, remote, safe, and easy to implement in testing and evaluation of various materials. This Letter presents the statistical post-processing approach for pulse compression favourable frequency modulated thermal wave imaging for inspection of mild steel samples having flat bottom hole defects. Furthermore, a detailed analysis has been carried out using independent component analysis and provides insight for choosing the number of independent components and number of eigenvalues to be retained in the whitening procedure. [ABSTRACT FROM AUTHOR]

Non-contact optical detection of ultrasound critically depends on the amount of light collected from the detection surface. Although it can be optimized in multiple ways for an ideal flat polished surface, industrial non-destructive testing and evaluation (NDT&E) usually requires optical detectors to be robust for unpolished material surfaces that are usually rough and curved. Confocal detectors provide the best light collection but must trade off sensitivity with depth of field. Specifically, detection efficiency increases with the numerical aperture (NA) of the detector, but the depth of field drops. Therefore, fast realignment of the detector focal point is critical for in-field applications. Here, we propose an optical distance and angle correction system (DACS) and demonstrate it in a kHz-rate laser-ultrasound inspection system. It incorporates a Sagnac interferometer on receive for the fast scanning of aircraft composites, which minimizes the required initial alignment. We show that DACS performs stably for different composite surfaces while providing ±2° angular and ±2 mm axial automatic correction with a maximum 100 ms realignment time.

Multilayer materials with metal–metal bonded structure have been widely applied in aviation, aerospace, and nuclear industry. Disbond is prone to exist in lead-steel bonded structure, which degrades the load capacity and mechanical behaviors. Thermography nondestructive testing is a potential candidate for sub-layer defect detection. However, lead-steel bonded structure is unbearable when undertaken with over-heating of instantaneous temperature, which will lead to subsequent damage or generation of more unpredictable disbond. In addition, detection sensitivity of the deeper defects requires to be enhanced. In this paper, the mathematical derivation and the implementation of the periodic pulsed thermography have been established for detecting inner defects of lead-steel structure. This has been especially conducted for detecting small and deep defects that require high energy to increase detectability. Validation of the proposed method has been undertaken on both inductive thermography and optical thermography. The obtained results have demonstrated that periodic pulsed thermography is highly efficient for deep inner defect inspection of metal–metal bonded structure. [ABSTRACT FROM PUBLISHER]

The detection and reconstruction of fatigue fractures is of great interest in quality assurance. In the framework of nondestructive testing, Lorentz force evaluation (LFE) is an evaluation technique to estimate flaws in electrically conductive materials based on measured Lorentz forces. In the forward solution for LFE, a defect can be interpreted as a distributed current source. This has motivated the authors to propose current density reconstructions (CDRs) calculated with minimum norm estimates to estimate defect geometries. TheL1andL2norms tend to produce a solution which is either very focused or very smeared. To balance these constraints, the generalLpnorm with 1 ≤p ≤2 was used and the inverse solutions compared. This approach was applied to measured data obtained from a laminated composite and simulated data from a monolithic material. The results show that theL1.5norm provides the most accurate inverse solutions. The location and extent of the defect are determined with an error of 15 % relative to the size of the defect. The depth estimation has a deviation of 50 %. It can be concluded that CDRs are a powerful method to reconstruct and characterize defects in LFE. [ABSTRACT FROM PUBLISHER]

Abstract: In order to prevent the danger caused by falling tiles from high-rise buildings, a rapid and effective non-destructive testing and evaluation (NDT&E) technique has been developed to assess the tile–wall bonding quality. The proposed technique is based on sounds excited by controlled impacts, and can easily be integrated with climbing robots to automate the tile–wall inspection process without the need for human workers to work at life-threatening height. To facilitate the result evaluation and maintenance planning, the approximate size of defective area needs to be assessed and determined. Though it is well-known that the natural frequency of flexural vibration is related to the size of the debonded area, strong multiple-mode frequencies caused by complex shapes of the defects or impacting at geometric edge (not at the center) of the defects impose significant difficulties in extracting automatically the natural frequency from the sound signals. In this paper, a fuzzy scheme is introduced to improve the robustness and accuracy of defects assessment. Based on fuzzy theory, vibration principle and human experience, a fuzzy logic model relating the characteristics of impact sounds to the approximate size of the defect is developed and utilized. The design of the fuzzy system, including membership functions and fuzzy reasoning rules, is also provided. To demonstrate the validity of the proposed method, experimental results obtained from physical tile walls are presented and discussed. [Copyright &y& Elsevier]

Abstract: Shearography has been widely adopted for nondestructive testing and evaluation of various materials, especially in the rubber industry and aerospace industry. It detects flaws and defects by identifying deformation anomalies when the specimen is stressed by a certain means. Conventional stressing methods for shearography include pressurization, mechanical or acoustic loading and vibration excitation. These stressing techniques are favorably applied in various applications. In this study, we propose a novel impulsive thermal stressing method using high-power flash lamps for convenient nondestructive testing and evaluation in both laboratory and industrial environment. The proposed technique employs a high-energy heat flux to excite the specimen and detects the thermal deformation anomaly using a shearographic setup. By incorporating a novel clustering phase extraction method, the movement of the continuously deforming object is obtained using only one single deformed speckle image at each deformed stage, thus enabling both qualitative and quantitative measurement. Experiments conducted on various samples with cracks and debonds demonstrate the practicability of proposed technique for both laboratory and industrial applications. [Copyright &y& Elsevier]

The noise suppression techniques with wavelet transform (WT) are widely used in nondestructive testing and evaluation (NDT&E), especially in ultrasonics. But the wavelet based filter has the property of equal Q-factor, so, it is impossible to choose the central frequency and the bandwidth arbitrarily at the same time. This paper develops a new technique using WT to eliminate this drawback. In this paper, a weak ultrasonic signals identification method by using the optimal parameter Gabor wavelet transform is proposed. We address the choice of the optimal central frequency and bandwidth of the Gabor wavelet using the kurtosis maximization algorithm. The central frequency and bandwidth of the optimal parameter Gabor wavelet matched that of the ultrasonic signal very well. Numerical and experimental results have been presented to evaluate the effectiveness of the optimal parameter Gabor wavelet transform on ultrasonic flaw detection. This technique is a simpler and effective technique for processing heavy noised ultrasonic signals. [ABSTRACT FROM AUTHOR]

Abstract: Various noise suppression techniques based on wavelet transform (WT) are widely used in non-destructive testing and evaluation (NDT&E). A weak ultrasonic signals identification method by using the optimal scale wavelet transform is proposed in this paper. The selection of the optimal scale is realized by maximizing the negentropy of the discrete wavelet transform (DWT) coefficients. The central frequency and bandwidth of the optimal scale wavelet matched that of the ultrasonic signal very well. Numerical and experimental results have been presented to evaluate the effectiveness of the optimal scale wavelet transform on ultrasonic flaw detection. This technique is a simpler and effective technique for processing heavy noised ultrasonic signals, and is greatly time-saving comparing with other typical wavelets transform. [Copyright &y& Elsevier]

Nondestructive testing and evaluation (NDT&E) are commonly used in the industry for their ability to identify damage and assess material conditions. Ultrasonic testing (UT) is one of the most popular NDT&E techniques. A variant of ultrasonic testing known as nonlinear ultrasonic testing (NUT) has some advantages over conventional (linear) UT as it is more sensitive to damages in their early stages; even at the microscopic levels. Furthermore, the nonlinear characteristics of ultrasonic waves can be correlated to several material properties. In the last two decades, the NUT method has been investigated from two aspects, namely the direct (modeling) problem and the inverse (NUT testing) problem. The direct problem aims to establish the nonlinear mechanism and analyze the behavior of wave-damage interaction. The inverse problem is investigated under three headings: (1) data acquisition with NUT techniques, (2) signal pre-processing and feature extraction, and (3) parameter analysis for damage characterization. The conventional data analytical methods extract nonlinear features from noisy signals and build a damage index to characterize damages. However, damage index-based analyzing model can be challenging, as other factors affect the overall system nonlinearity such as complex specimen geometry, different damage characteristics, varying ambient conditions, and measurement uncertainties. To overcome these shortcomings, machine learning (ML) methods appear promising for the analysis of complex nonlinear ultrasonic signals by exploiting data mining and pattern recognition capabilities. Therefore, this paper aims to provide a comprehensive review of the state-of-the-art ML-enriched NUT for damage characterization. Other NUT-based technologies are also reviewed, including modeling of wave-damage interaction, different NUT techniques for data acquisition, signal pre-processing methods, and damage index-based parameter analysis strategies for damage characterization. Major emphasis is placed on the application of ML methods for NDT&E applications. Additionally, future research trends on data augmentation, complex damage characterization, and baseline-free methods using NUT are also discussed. • The nonlinear ultrasonic testing is reviewed under direct and inverse problem. • The data analytics for damage characterization are reviewed. • The machine learning methods for damage characterization are reviewed. • The trends of ML-enriched NUT for damage characterization are discussed. [ABSTRACT FROM AUTHOR]

The long-term research experience of the authors has highlighted the importance of gaining knowledge of the building through experimental investigation. Recently the authors intensively studied the Syracuse Cathedral (Sicily, Italy) to evaluate the structural state of the preservation of the pillars. The Cathedral of Syracuse was built in different phases on an ancient Greek temple from the fifth century bc and modified throughout later centuries. The pillars of the central nave, obtained by cutting the temple cell walls, show a complex situation of damage and repairs. An investigation program (including radar, sonic, and ultrasonic tests, for example) has been recently planned, aimed to design the preservation and restoration actions. An accurate geometric survey of the surface problems and defects allowed the localization of the most damaged area, suggesting the need for further control by non-destructive testing (NDT). The results obtained from this survey were compared with the results of the other type of tests, and the elaborated data will be used to implement an analytical model for the study of the seismic vulnerability. The preliminary results of the experimental investigation carried out by the authors are presented in this article. [ABSTRACT FROM AUTHOR]

Abstract: Magnetic flux leakage (MFL) techniques have been widely used for non-intrusively inspecting steel installations by applying magnetization. In the situations where defects may take place on the near and far surfaces of the structure under inspection, current MFL techniques are unable to determine their approximate size. Consequently, an extra transducer may have to be included to provide the extra information required. This paper presents a new approach termed as pulsed magnetic flux leakage (PMFL) for crack detection and characterisation. The probe design and method are introduced. The signal features in time–frequency domains are investigated through theoretical simulations and experiments. The results show that the technique can potentially provide additional information about the defects. Lastly, potential applications are suggested. [Copyright &y& Elsevier]

Transient-pulsed thermography was used as a through skin imaging technique with the intention of locating anchoring points beneath the outer skins of aircraft structures. A representative test structure, comprising a thin skin positioned over a thick strut fixture, was investigated experimentally and analysed using finite difference thermal modelling software. Both carbon fibre reinforced plastic (CFRP) and aluminium structures were investigated. The ability of the technique to detect a subsurface fixing and to provide information about its location was analysed. Results indicate a precision of better than 0.5 mm to be achievable. [Copyright &y& Elsevier]

After an earthquake, which struck the Eastern part of Sicily in 1990, some structural elements of the Church of S. Nicolo` l'Arena in Catania, as the dome and the vaults, were damaged; vertical cracks on the two pillars were detected. It is not clear whether those cracks were already visible and were simply propagating during the earthquake. It is known that the two pillars probably belong to the original construction of the church.An investigation programme (including historical research and experimental investigation with sonic, radar, flat-jack, coring, boroscopy, etc.) has been recently planned to design the preservation and restoration actions.The results obtained from sonic tests were compared to the results of the other type of tests in order to set up an investigation procedure useful for these cases. The paper presents and discusses the preliminary results of the research carried out by the authors. [Copyright &y& Elsevier]

Non-contact optical detection of ultrasound critically depends on the amount of light collected from the detection surface. Although it can be optimized in multiple ways for an ideal flat polished surface, industrial non-destructive testing and evaluation (NDT&E) usually requires optical detectors to be robust for unpolished material surfaces that are usually rough and curved. Confocal detectors provide the best light collection but must trade off sensitivity with depth of field. Specifically, detection efficiency increases with the numerical aperture (NA) of the detector, but the depth of field drops. Therefore, fast realignment of the detector focal point is critical for in-field applications. Here, we propose an optical distance and angle correction system (DACS) and demonstrate it in a kHz-rate laser-ultrasound inspection system. It incorporates a Sagnac interferometer on receive for the fast scanning of aircraft composites, which minimizes the required initial alignment. We show that DACS performs stably for different composite surfaces while providing ±2° angular and ±2 mm axial automatic correction with a maximum 100 ms realignment time. [ABSTRACT FROM AUTHOR]

Concrete failure will lead to serious safety concerns in the performance of a building structure. It is one of the biggest challenges for engineers to inspect and maintain the quality of concrete throughout the service years in order to prevent structural deterioration. To date, a lot of research is ongoing to develop different instruments to inspect concrete quality. Detection of moisture ingress is important in the structural monitoring of concrete. This paper presents a novel sensing technique using a smart antenna for the non-destructive evaluation of moisture content and deterioration inspection in concrete blocks. Two different standard concrete samples (United Kingdom and Malaysia) were investigated in this research. An electromagnetic (EM) sensor was designed and embedded inside the concrete to detect the moisture content within the structure. In addition, CST microwave studio was used to validate the theoretical model of the EM sensor against the test data. The results demonstrated that the EM sensor at 2.45 GHz is capable of detecting the moisture content in the concrete with linear regression of R2 = 0.9752. Furthermore, identification of different mix ratios of concrete were successfully demonstrated in this paper. In conclusion, the EM sensor is capable of detecting moisture content non-destructively and could be a potential technique for maintenance and quality control of the building performance. [ABSTRACT FROM AUTHOR]

Laser-ultrasonics is an attractive and powerful tool for the non-destructive testing and evaluation (NDT&E) of composite materials. Current systems for non-contact detection of ultrasound have relatively low sensitivity compared to contact peizotransducers. They are also expensive, difficult to adjust, and strongly influenced by environmental noise. Moreover, laser-ultrasound (LU) systems typically launch only about 50 firings per second, much slower than the kHz level pulse repetition rate of conventional systems. As demonstrated here, most of these drawbacks can be eliminated by combining a new generation of compact, inexpensive, high repetition rate nanosecond fiber lasers with new developments in fiber telecommunication optics and an optimally designed balanced probe beam detector. In particular, a modified fiber-optic balanced Sagnac interferometer is presented as part of a LU pump-probe system for NDT&E of aircraft composites. The performance of the all-optical system is demonstrated for a number of composite samples with different types and locations of inclusions.