An alternating current potential drop technique is presented that exploits anisotropic magnetostriction to monitor changes in applied stress in steel. The background to the technique is provided together with an ad hoc approximation that describes the sensitivity of the sensor to the underlying properties. A uniaxial loading experiment has been conducted on duplex and mild steel specimens showing that changes in stress are measureable. Saturation and hysteresis afflict the measurement, which, in addition to sensitivity to temperature and magnetisation, may undermine inversion. With the capabilities and limitations of the proposed technique introduced, guidance on possible suitable applications are given, concluding that use for monitoring the number and relative size of fatigue stress cycles may be a suitable and attractive opportunity.

A feasibility study on grain noise suppression using baseline subtraction is presented in this paper. Monitoring is usually done with permanently installed transducers but this is not always possible; here instead monitoring is conducted by carrying out repeat C-scans and the feasibility of grain noise suppression by subtracting A-scans extracted from the C-scans is investigated. The success of this technique depends on the ability to reproduce the same conditions for each scan, including a consistent stand-off, angle, and lateral position of the transducer relative to the testpiece. The significance of errors are illustrated and a 3D cross correlation is used which enables the same lateral position to be located within successive C-scans. The experimental results show that a noise reduction of around 15 dB is obtained after baseline subtraction, which will significantly improve the defect detection sensitivity. In practice however, successive C-scans may be conducted at different temperatures and with different transducers of similar specifications but a varying frequency response. Compensation techniques to reduce the impact of such variations are then presented and their effectiveness is verified experimentally. It is shown that it is feasible to obtain an overall improvement of around 10 dB in the signal to noise ratio via baseline subtraction, where a temperature difference of up to 10  C and a peak frequency shift of as much as ±250 kHz from a baseline value of around 7 MHz can be tolerated. However, this improvement was obtained in laboratory conditions with no changes to the surface of the specimen due to oxidation or corrosion. It is shown that differences in temperature and transducer frequency response are more difficult to compensate for than changes in test geometry and position.

A model for the amplitude and phase of ultrasonic tone-bursts incident on adherend-adhesive interfaces is developed for both reflected and transmitted waves. The model parameters include the interfacial stiffness constants, which characterize the elastic properties of idealized adherend-adhesive interfaces having a continuum of bonds. The ultrasonic model is linked to the more realistic physico-chemical model of adhesive bonding via a scaling equation that establishes the relationship between the interfacial stiffness constants of the ultrasonic model and the fraction of actual bonds in the physico-chemical model. The link to the physico-chemical model enables a quantitative assessment of the absolute bond strength. The ultrasonic model and scaling equation are applied to the simulation assessment of the absolute bond strength of two aluminum alloy adherends joined by an epoxy adhesive. Model input is obtained from the calculated phase of tone-bursts reflected from the adherend-adhesive interfaces as a function of the interfacial stiffness constants. The simulation shows that the reflected phase is dominated by the first interface encountered by the incident tone-burst with little contribution from the second interface. The simulation also shows that the accuracy in assessing the adhesive bond strength depends on the sensitivity of the reflected phase to variations in the interfacial stiffness constants, reflecting in part the nonlinearity of the scaling relationship.

In this research, ultrasonic pulse echo measurements are used to quantify through thickness chemical degradation in thin mortar specimens. The degradation level is predicted using the time of travel of the acoustic wave through the thickness of the structure. The front and back wall interaction reflections are used to obtain additional information from very early stage degradation. The pulse-velocity of sound waves as a function of the thickness of the layers within the structure is described. With knowledge of the pulse-velocity in pristine and fully degraded conditions, it is possible to determine the complete range of degradation length over the layer thickness. The method is applicable for leaching of calcium and acidic attack. The acoustic measurements were verified with destructive testing. The correlation between the acoustic and non-acoustic experiments agree with the described pulse-velocity and degraded depth function. The method based on ultrasonic measurements can be implemented in other thin-layered structures.

The present study explores the capability of COMSOL Multiphysics, as a finite element modelling (FEM) tool, to model the interaction between a split-D differential surface eddy current (ECT) probe and semi-elliptical surface electrical discharge machined (EDM) notches. The effect of the small probe's lift-off and tilt on its signal is investigated through modelling and subsequently, the simulation outcomes are validated using the probe's impedance measurements. In the next stage, an adaptive neuro-fuzzy inference system (ANFIS) is designed to take the signal features as inputs and consequently, provide the length of the scanned notch as the system's output. The system is trained by extracted features of thirty model-generated signals obtained from scanning of the same number of semi-elliptical notches by means of the split-D probe. The trained ANFIS is tested afterwards using the measured signals of 3 calibration EDM notches together with 5 model-based ones. A very low average estimation error is observed with regard to the length estimation of the test notches and the accuracy of the length estimation is found to be quite reasonable.

We present a new approach to estimate geometry parameters of glass fibers in glass fiber-reinforced polymers from simulated X-ray micro-computed tomography scans. Traditionally, these parameters are estimated using a multi-step procedure including image reconstruction, pre-processing, segmentation and analysis of features of interest. Each step in this chain introduces errors that propagate through the pipeline and impair the accuracy of the estimated parameters. In the approach presented in this paper, we reconstruct volumes from a low number of projection angles using an iterative reconstruction technique and then estimate position, direction and length of the contained fibers incorporating knowledge about their shape, modeled as a geometric representation, which is then optimized. Using simulation experiments, we show that our method can estimate those representations even in presence of noisy data and only very few projection angles available.

Differential eddy current probes are commonly used to detect shallow surface cracks in conductive materials. In recent years, a growing number of research works on their numerical modelling was conducted since the development of analytical or semi-analytical models for such a sensor may be prone to intractable complications. In this paper finite element modelling (FEM) has been employed to simulate the interaction of a reflection differential split-D probe with surface electrical discharge machined (EDM) notches in 3-dimensional (3-D) half-space. In order to attain a better insight into the correct setup of the FEM parameters, a simple multi-turn cylindrical absolute coil has also been modelled. The outcome generated through the simulated scan of this absolute coil over a surface notch in aluminum is validated with existing experimental impedance data taken from the literature. Parameters contributing to reliable FEM simulation results, such as maximum mesh size, mesh distribution, the extent of the surrounding air domain and conductivity of the air are investigated for the 3-D modelling of both absolute and differential probes. This study shows that the simulation results on a commercial reflection differential split-D surface pencil probe closely estimate the experimental measurements of the probe's impedance variations as it scans three EDM notches having different depths in aluminum. The simulation results, generated by Comsol Multiphysics FEM package (COMSOL I, COMSOL multiphysics reference manual, version 5.3, COMSOL AB, 2018, www.comsol.com), for the cases of absolute and differential probes are checked for their extent of validity.

Applying life estimation approaches to determine in-service life of structures and plan the inspection schedules accordingly are becoming acceptable safety design procedures in aerospace. However, these design systems shall be fed with reliable parameters related to material properties, loading conditions and defect characteristics. In this context, the role of non-destructive (NDT) testing reliability is of high importance in detecting and sizing defects. Eddy current test (ECT) is an electromagnetic NDT method frequently used to inspect tiny surface fatigue cracks in sensitive industries. Owing to the new advances in robotic technologies, there is a trend to integrate the ECT into automated systems to perform NDT inspections more efficiently. In fact, ECT can be effectively automated as to increase the coverage, repeatability and scanning speed. The reliability of ECT scanning, however, should be thoroughly investigated and compared to conventional modes of applications to obtain a better understanding of the advantages and shortcomings related to this technique. In this contribution, a series of manual and automated ECT tests are carried out on a set of samples using a split-D reflection differential surface probe. The study investigates the level of noise recorded in each technique and discuss its dependency on different parameters, such as surface roughness and frequency. Afterwards, a description of the effect of crack orientation on ECT signal amplitude is provided through experimental tests and finite element simulations. Finally, the reliability of each ECT technique is investigated by means of probability of detection (POD) curves. POD parameters are then extracted and compared to examine the effect of scanning index, frequency and automation on detection reliability.

Convolutional neural networks were used for multiclass segmentation in thermal infrared face analysis. The principle is based on existing image-to-image translation approaches, where each pixel in an image is assigned to a class label. We show that established networks architectures can be trained for the task of multiclass face analysis in thermal infrared. Created class annotations consisted of pixel-accurate locations of different face classes. Subsequently, the trained network can segment an acquired unknown infrared face image into the defined classes. Furthermore, face classification in live image acquisition is shown, in order to be able to display the relative temperature in real-time from the learned areas. This allows a pixel-accurate temperature face analysis e.g. for infection detection like Covid-19. At the same time our approach offers the advantage of concentrating on the relevant areas of the face. Areas of the face irrelevant for the relative temperature calculation or accessories such as glasses, masks and jewelry are not considered. A custom database was created to train the network. The results were quantitatively evaluated with the intersection over union (IoU) metric. The methodology shown can be transferred to similar problems for more quantitative thermography tasks like in materials characterization or quality control in production.

Cyber technologies are offering new horizons for quality control in manufacturing and safety assurance in-service of physical assets. The line between non-destructive evaluation (NDE) and Industry 4.0 is getting blurred since both are sensory data-driven domains. This multidisciplinary approach has led to the emergence of a new capability: NDE 4.0. The NDT community is coming together once again to define the purpose, chart the process, and address the adoption of emerging technologies. In this paper, the authors have taken a design thinking approach to spotlight proper objectives for research on this subject. It begins with qualitative research on twenty different perceptions of stakeholders and misconceptions around the current state of NDE. The interpretation is used to define ten value propositions or use cases under 'NDE for Industry 4.0' and 'Industry 4.0 for NDE' leading up to the clarity of purpose for NDE 4.0-enhanced safety and economic value for stakeholders. To pursue this worthy cause, the paper delves into some of the top adoption challenges, and proposes a journey of managed innovation, conscious skills development, and a new form of leadership required to succeed in the cyber-physical world.

The challenges presented by the global pandemic and slump in oil prices have imposed costly avoidance measures and delayed project timeliness, but it also has created the opportunity for innovation conditions in industrial non-destructive testing. The evolutional path leveraged by Industry 4.0, present sustainable offerings of robotic platforms, digital solutions and connected devices commonly known as the Internet of Things (IoT) that may assist in recapturing some of the current losses. The landscape is broad with staggered adoptions. An overview of the Industrial Revolutions, related developments in NDE 4.0 and specific focus on North American radiography in the petroleum industry is highlighted. Additionally, focusing on the importance of shared transparency and burden throughout the value-chain to ensure efficacy throughout the migration, and the human contributor for collaborative transition and skills required for the future. The evolutional path of Industrial revolutions leads to Industry 4.0 which presents opportunities with Artificial Intelligence, and connected devices commonly known as the Internet of Things (IoT). This article focuses on three major issues for consideration in the development of a strategic plan to capitalize on the advancements of digital radiography in the petroleum sector. The components are the technological NDE 4.0 transformation, the need for a new and realistic perspective of digital radiography, and the challenges of developing a workforce to adapt to the transition of NDE 4.0.

Across so many industries, non-destructive evaluation has proven its worth time and again through quality and safety assurance of valuable assets. Yet, over time, it became underappreciated in business decisions. In most cases, the data gathered by NDT is used for quality assurance assessments resulting in binary decisions. And we seem to miss out on value of the information content of NDE which goes way deeper and can help other stakeholders: such as engineering, management, inspectors, service providers, and even regulators. Some of those groups might not even be aware of the benefits of NDE data and its digitalization. Unfortunately, the NDE industry typically makes the data access unnecessarily difficult by proprietary interfaces and data formats. Both those challenges need to be addressed now by the NDE industry. The confluence of NDE and Industry 4.0, dubbed as NDE 4.0, provides a unique opportunity for the NDE/NDT Industry to not only readjust the value perception but to gain new customer groups through a broad set of value creation activities across the ecosystem. The integration of NDE into the Cyber-Physical Loop (including IIoT and Digital Twin) is the chance for the NDE industry to now shift the perception from a cost center to a value center. This paper provides an overview of the NDE ecosystem, key value streams, cyber-physical loops that create value, and a number of use cases for various stakeholders in the ecosystem.

The determination of the mechanical properties of materials is predominantly undertaken using destructive approaches. Such approaches are based on well-established mathematical formulations where a physical property of the material is measured as a function of an input under controlled conditions provided by some machine, such as load-displacement curves in indentation tests and stress-strain plots in tensile testing. The main disadvantage of these methods is that they involve destruction of samples as they are usually tested to failure to determine the properties of interest. This means that large sample sizes are required to obtain statistical certainty, a condition that, depending on the material, may mean the process is both time consuming and expensive. In addition, for rapid prototyping and small-batch manufacturing of polymers, these techniques may be inappropriate either due to excessive cost or high polymer composition variability between batches. In this paper we discuss how the Euler-Bernoulli beam theory can be exploited for experimental, non-destructive assessment of the mechanical properties of three different 3D-printed materials: a plastic, an elastomer, and a hydrogel. We demonstrate applicability of the approach for materials, which vary by several orders of magnitude of Young's moduli, by measuring the resonance frequencies of appended rectangular cantilevers using laser Doppler vibrometry. The results indicate that experimental determination of the resonance frequency can be used to accurately determine the exact elastic modulus of any given 3D-printed component. We compare the obtained results with those obtained by tensile testing for comparison and validation.

We investigated the force produced by a conical piezoelectric (PZT, lead zirconate titanate) transducer actuated by high voltage pulses (HVP) in contact with a steel transfer plate. Using elastic wave propagation theory in a semi-infinite plate, we aimed to quantify the magnitude and estimate the shape of the force-time function via the body waves produced in the transfer plate using the displacement field recorded on an array of 20 absolutely calibrated PZT receivers. We first calibrated the receiver array using glass capillary fracture. We proceeded to use a conical PZT transducer to actively produce a source at the origin, allowing us to study the displacement field produced on the now calibrated PZT receiver array. We studied two types of HVP: An impulsive and step source. The calibrated receiver array was used to estimate the general shape of the force-time functions for each type of HVP. From our hypothesized force-time functions we were able to estimate the peak force produced by the PZT actuator: The impulsive source generated a force of N and the step source generated N, respectively, for a peak applied voltage of 273 V. This translates to an applied force of 0.011 N/V and 0.007 N/V for the impulse and step force-time functions, respectively, which is similar to estimates found in the literature for other conical transducers in contact with metallic transfer media. This measurement was verified directly by independent measurements of the peak force using a dynamic force transducer. We found that our methodology correctly estimated the magnitude of the force but is limited to transducers with incident angles 53 . Beyond this angle, overestimates of the force were observed due to the lack of body wave energy produced by the source. These results allow us to quantitatively determine the forces produced by active PZT techniques using only the measurement of the displacement field captured on a calibrated conical PZT array. Quantitative understanding of active PZT sources additionally constrains the transfer functions approach, which is commonly used in the non-destructive testing of materials and in other fields, such as rock physics and laboratory seismology.

Non-destructive stress measurement by ultrasonic testing is based on calculating the acoustoelastic modulus obtained from the relationship between material stress and sound wave velocity. A critically refracted longitudinal (L) wave, which is a bulk longitudinal wave penetrating below and parallel to the surface below an effective depth, is most suitable for ultrasonic stress measurement tests because it exhibits a relatively large change in travel time in response to a change in stress. In particular, the residual stress distribution through the thickness of the subject can be calculated if transducers of different frequencies are applied because of the characteristic of propagation to different depths of penetration depending on the frequency. The main purpose of this study was to visualize the internal or residual stress distribution through the thickness of rails using L waves. To this end, L probes with different center frequencies were designed and manufactured, and the residual stress values ​​of an unused railroad rail and two used railroad rails operated under different conditions were calculated. This was done using the ultrasonic signals received from each probe, of which the distributions were mapped. Through these mapping results, different residual stress values could be calculated according to the depth. The differences in residual stress generation and distribution according to the conditions surrounding the contact between train wheels and rails, and their characteristics, were visualized and analyzed. As a result, it could be concluded that the non-destructive evaluation technique using L waves could detect differences in the residual stress of a rail, and thus can be used to measure the residual stress of the rail accurately.