Nondestructive Testing Evaluation Research Articles

Improved long pulse excitation infrared nondestructive testing evaluation.

In this paper, an improved long-pulse excitation infrared nondestructive testing method is proposed, and a homogeneous pulse thermography (HPT) system is built. Based on the proposed new pulse excitation system, the problem of uneven heating in pulsed infrared non-destructive testing (NDT) has been effectively improved, and the signal-to-noise ratio of thermal images has been improved. Finally, the results of the experimental analysis and discussion show that the improved pulsed infrared NDT system greatly improves the defect detection rate and the reliability of the quantitative analysis of defect depth compared with the traditional pulsed detection system.

Tips for Effective Machine Learning in NDT/E

The proliferation of machine learning (ML) advances will have long-lasting effects on the nondestructive testing/evaluation (NDT/E) community. As these advances impact the field and as new datasets are created to support these methods, it is important for researchers and practitioners to understand the associated challenges. This article provides basic definitions from the ML literature and tips for nondestructive researchers and practitioners to choose an ML architecture and to understand its relationships with the associated data. By the conclusion of this article, the reader will be able to identify the type of ML architecture needed for a given problem, be aware of how characteristics of the data affect the architecture’s training, and understand how to evaluate the ML performance based on properties of the dataset.

Benefits and Concerns of Using Emerging Artificial Intelligence Chatbots With Work in NDT

While most of the papers in this special issue explore the use of artificial intelligence and machine learning (AI/ML) to support the evaluation of nondestructive testing (NDT) data and assist with the classification of NDT indications, there are other important ways that emerging AI tools may impact how we work in NDT. The article discusses the recent emergence of AI chatbots, also referred to as generative artificial intelligence agents or large language models (LLMs), and highlights the potential benefits and risks as part of work in the NDT field.

Evaluation Method for the UV Aging State of Composite Insulators Based on Hyperspectral Characteristic

Strong ultraviolet (UV) radiation is one of the main factors that lead to the aging of composite insulators of transmission lines in high altitude areas, which has brought security risks to the operation of power systems. The aging status information obtained by traditional insulation surface aging detection methods is indirect and limited, or time-consuming and labor-intensive. In this paper, a non-contact nondestructive testing evaluation method based on hyperspectral technology is proposed to quickly detect the UV aging state of composite insulator surface. Firstly, the hyperspectral imaging platform is used to image a number of continuous bands on the insulator surface. Combining the aging calibration data, a locally reserved projection-convolutional neural network (LPP-CNN) model is established to to extract the characteristic bands of aging surface and provide a way to accurately evaluate surface UV aging degree of insulators. The model has a high resolution of aging degree, which provides a new idea and theoretical basis for realizing non-contact non-destructive online detection of surface aging under ultraviolet light.

Critical evaluation of NDT for rapid condition assessment of existing RC buildings: A case study

There is an urgent need for rapid and reliable condition assessment of existing reinforced concrete (RC) buildings as a basis for structural safety evaluation, especially in developing countries in seismic regions such as Turkey. Traditionally, RC structures are evaluated by taking core samples from a limited number of structural elements for concrete strength and performing spot checks for the steel reinforcement by removing the concrete cover. In-situ concrete strength is determined through compression testing of core samples. Through spot checks, conformance of the existing reinforcement with the structural drawings is evaluated and a reinforcement realization factor is calculated for use in the analyses. Even though these conventional methods are relatively more accurate and reliable for condition assessment of existing RC structures, they are destructive, involved, time taking, slow and expensive. Non-destructive testing (NDT) methods are proposed as a solution to this problem. Using NDT methods in conjunction with a relatively small number of core tests potentially allows for more rapid yet still reliable condition assessment of existing structures. In this paper, a critical evaluation of rapid and reliable condition assessment methods is made through investigations on an 18-story residential RC building as a case study. Investigation results show that using NDT helps achieve time and cost savings while allowing for reliable condition assessment of existing buildings, and promises further savings through continued research and development in this area.

Numerical and Non-Destructive Analysis of an Aluminum-CFRP Hybrid 3D Structure

Advanced materials are widely used in many industries. They play an important role especially in the aeronautic and automotive sectors where weight reduction is required in order to reduce fuel consumption. Composite materials have a high strength to weight ratio and are applied in airplane construction. Nevertheless, sometimes it is not viable to replace all metal parts by composite ones due to the cost factor. In this sense, hybrid structures are highly welcome. In order to ensure the safety of these hybrid components during their entire life cycle, non-destructive testing evaluation (NDT&E) methods are used and sometimes they are the only option. In this study, we use infrared thermography (IRT) to inspect an aluminum-composite hybrid structure with a 3D shape. The sample has a composite part with a small metal inlay (EN AW-6082) overmolded with a thermoplastic layer. The inlay is bended to reach the desired 3D geometry. This sample was design to be used for the connection between an A- or B-pillar and a car roof made of carbon fiber reinforced polymer (CFRP). A dual-band infrared camera is used in order to capture images in two different spectral ranges. In addition, two data processing techniques for infrared images are applied to enhance the images: principal component thermography (PCT) and partial least squares thermography (PLST). Then, a signal-to-noise ratio analysis is performed with three randomly chosen previous known defects to assess the quality of the images and detected defects. Results showed that principal component thermography has a slight advantage over partial least squares thermography in our specific experiments. Specifically, for the long-wave infrared band, PCT presented, among the defects analyzed, PCT presented a mean value 12.5% higher while the standard deviation was almost three times lower than PLST. In parallel to the non-detructive analysis, a numerical finite element model was formulated in ANSYS® to analyze the total deformations to which the metal-composite-hybrid structure is subjected during a possible use. Results obtained with the numerical model indicate that the interface region between composite and metal parts is where the highest degree of deformation occur, which indicates possible regions where defects and failures may occur in real use cases.

Digital clone testing platform for the assessment of SHM systems under uncertainty

The performance of a Structural Health Monitoring (SHM) system can be assessed using Probability of Detection (PoD) curves, which is a common tool for the evaluation of Non-Destructive Testing (NDT) methods. This study presents a novel digital clone platform to quantify and account for uncertainties that can be detrimental to the reliability of a SHM system. Uncertainties relating to experimental measurement noise and Environmental and Operational Conditions (EOC) are considered during the definition of a threshold value that aims at reliably distinguishing between pristine and damaged signals. At the same time, the variability of impact damage characteristics and uncertainties associated with Lamb waves interaction in composites are captured though the Bayesian calibration of a Finite Element (FE) model using experimental observations. The FE model is integrated within the digital clone testing platform to substitute the experimental testing and generate a statistical sample of distributed impact events at different locations on a composite plate and compute the Model Assisted Probability of Detection (MAPOD). This approach allows the estimation of the system’s performance under different EOC that can be used during the selection and operation of a specific SHM configuration.

The Study of Concrete Mixture Performance to Support the Non-Destructive Testing Evaluation

An experimental program is conducted which three type of concrete mixtures are made to express the different in quality of concrete. Each type of concrete mixture will be consisting of two type of specimens, i.e., ∅100mm × 200mm in height and ∅150mm × 300mm in height. Each set will be 30 specimens, so the total specimens are 180. All the specimens will be tested in the standard age of 28 days. All of them will be tested as follow: (1) Rebound hammer test, (2) ultrasonic pulse velocity, and (3) compressive test. The ∅100mm test specimens having correlation ranged from 90% to 95% against ∅150mm test specimens. The rebound number of Schmidt hammer test having good correlation to the compression strength since it has the R2 of 0.8259, so that the regression value to be 0.9088. The ultrasonic pulse velocity reading also having good correlation to the compression strength since it has the R2 of 0.8006, so that the regression value to be 0.8946. The combine between rebound number, ultrasonic pulse velocity against the compression strength, after being normalize and analyse using nonlinear dynamic regression, having the good correlation since it has the R2 of 0.9843 and so that the regression value to be 0.9921. The chart produced from the nonlinear dynamic regression can be used directly to predict the concrete compression strength from the rebound number and the reading of ultrasonic pulse velocity.

Analytical modeling of flexible structures for health monitoring under environmentally induced loads

Wireless structural health monitoring (SHM) represents an emerging paradigm in non-destructive testing evaluation, which is regularly performed within the framework of structural maintenance of critical infrastructure. While traditional cable-based SHM strategies have largely relied on centralized structural response data collection and processing, in wireless SHM the sensor nodes essentially operate as stand-alone processing units. Furthermore, the on-board processing capabilities of wireless sensor nodes have been widely exploited for decentralizing SHM tasks, thus avoiding power-consuming wireless transmission of entire structural response data sets. Evidently, on-board processing requires approaches tailored to the limited computational resources of wireless sensor nodes, particularly for computationally intensive, state-of-the-art strategies for SHM that rely on artificial intelligence (AI). Specifically, in model-based SHM/AI strategies, AI algorithms are trained by running the so-called what-if scenarios using numerical models of monitored structures. However, the use of numerical models in a decentralized wireless SHM scheme might be prohibitive from a computational resources point of view. To overcome this limitation, analytical modeling techniques using elastic waveguides are developed here that carry a low computational burden. These are specifically tailored for flexible structures of variable cross section, which comprise typical components of critical infrastructure such as masts, antennas and pylons, and can be used for simulating axial, torsional and flexural vibrations. The accuracy and efficiency of the proposed analytical modeling approach are then demonstrated through comparisons with conventional numerical models based on the finite element method.

Nondestructive Evaluation of 2 by 8 and 2 by 10 Southern Pine Dimensional Lumber

Abstract This study investigated the use of two nondestructive testing (NDT) methods to evaluate the mechanical properties of No. 2 grade: 2 by 8 and 2 by 10 southern pine lumber. The dynamic modulus of elasticity (dMOE) of each specimen was evaluated nondestructively by using longitudinal vibration and transverse vibration in edgewise and flatwise directions. After the NDT evaluation, the specimens were destructively tested and correlations between static bending MOE with modulus of rupture (MOR) and dMOE were developed. The overall MOE values were 11.14 and 10.96 GPa for 2 by 8 and 2 by 10, respectively. For MOR, the overall value for 2 by 8 was 42.59 MPa, and for 2 by 10 was 43.05 MPa. As expected, results showed statistically significant correlations between static MOE and dMOE (with r ranging from 0.87 to 0.96 for both sizes tested). Also as expected, weaker correlations were found between MOR and the dMOE values (with r ranging from 0.42 to 0.57 for both sizes tested). The lower correlations are largely explained by the difference between the NDT tools analyzing each specimen's global stiffness versus MOR, which is influenced heavily by localized characteristics. Perhaps this finding occurred because larger strength-reducing characteristics are permitted in larger section pieces (2 by 8 vs. 2 by 10) and thus they have opportunity for greater variability. The continuation of studies to develop more reliable NDT is crucial to improve the evaluation of mechanical properties of southern pine lumber and is beneficial to the southern pine timber industry.

Assessment of Functional Capacity of Metallic Articles Following Long-Term Service

A method of non-destructive testing for evaluation of the state of the material of metallic articles in the course of service is described. The method is based on control of plastic hardness.

Dual Gaussian attenuation model of ultrasonic echo and its parameter estimation

Signal de-noising and feature extraction, whose performance directly affect the evaluation of non-destructive testing (NDT) results, is essential technology for ultrasonic NDT echo processing. Aiming to solve the problem of nonlinear distortion between measured ultrasonic echo and its mathematical model, which widely used are exponential model (EM) and Gauss model (GM), a dual Gaussian attenuation model (DGAM) of ultrasonic echo signal and its parameter estimation method are proposed in this paper. The proposed dual Gaussian attenuation model parameter estimation (DGAM-PE) method is introduced in three parts: calculating mean square error between measured signal and model, optimizing mean square error by particle swarm optimization, optimum parameters extraction based on optimization result. The simulation and experiment results show that compared with the exponential model and Gaussian model, the proposed dual gaussian attenuation mathematical model of ultrasonic signal in this paper can better simulate the measured ultrasonic echo signal, with a mean square error of 0.0073 and normalized correlation coefficient of 0.9816. Additionally, an improved adaptive particle swarm optimization is proposed in order to enhance the accuracy of parameter estimation results.

An Improved Technique for Elastodynamic Green's Function Computation for Transversely Isotropic Solids

Elastodynamic Green's function for anisotropic solids is required for wave propagation modeling in composites. Such modeling is needed for the interpretation of experimental results generated by ultrasonic excitation or mechanical vibration-based nondestructive evaluation tests of composite structures. For isotropic materials, the elastodynamic Green’s function can be obtained analytically. However, for anisotropic solids, numerical integration is required for the elastodynamic Green's function computation. It can be expressed as a summation of two integrals—a singular integral and a nonsingular (or regular) integral. The regular integral over the surface of a unit hemisphere needs to be evaluated numerically and is responsible for the majority of the computational time for the elastodynamic Green's function calculation. In this paper, it is shown that for transversely isotropic solids, which form a major portion of anisotropic materials, the integration domain of the regular part of the elastodynamic time-harmonic Green's function can be reduced from a hemisphere to a quarter-sphere. The analysis is performed in the frequency domain by considering time-harmonic Green's function. This improvement is then applied to a numerical example where it is shown that it nearly halves the computational time. This reduction in computational effort is important for a boundary element method and a distributed point source method whose computational efficiencies heavily depend on Green's function computational time.

Laboratory assessment of nine methods for nondestructive evaluation of concrete bridge decks with overlays

Overlay systems have been extensively used to extend the service life of concrete bridge decks. There is, however, a lack of systematic studies on nondestructive evaluation (NDE) of concrete bridge decks with various overlays. This study assesses nine NDE methods for evaluation of concrete bridge decks with seven different types of overlays through laboratory concrete specimens. The nine NDE methods are sounding, ultrasonic surface waves (USW), impact echo (IE), ultrasonic testing (UT), impulse response (IR), ground-penetrating radar (GPR), electrical resistivity (ER), half-cell potential (HCP), and infrared thermography (IRT). The seven types of overlays are epoxy, latex modified concrete, silica fume modified concrete, polyester polymer, asphalt with a liquid membrane, asphalt with a sheet membrane, and asphalt without a membrane. Eight concrete specimens with various defects were built and nondestructively evaluated to acquire the detailed information of all embedded defects before placing overlays. One concrete specimen was kept bare as a reference, and the other seven specimens were covered with seven different overlays, respectively. Half of each overlay was bonded to the underlying concrete specimens, whereas the other half was debonded. NDE tests were carried out on the top of overlays. Based on the NDE test results, the applicability of each NDE method for concrete bridge decks with overlays is summarized as follows: (1) GPR and HCP are two effective methods for evaluation of the underlying concrete decks through both bonded and debonded overlays; (2) USW, IE, and UT can image the defects in the underlying concrete decks under bonded overlays, with the exception of the three asphalt overlays; (3) sounding, IR, and IRT can identify overlay debonding; and (4) ER is not effective due to electrical insulation of the overlay materials.

Two-tier data fusion method for bridge condition assessment

Fusing collected inspection data provides comprehensive and relatively more accurate diagnostics of defects and accordingly more accurate condition assessment of structures. This paper presents a new two-tier method that utilized data fusion methods for condition assessment of reinforced concrete bridge decks. The method utilizes pixel and feature levels fusion of data collected from multiple nondestructive evaluation (NDE) methods such as ground penetrating radar, impact echo, half-cell potential, and electrical resistivity. Data and measurements of NDE methods are extracted from the Iowa Highway research board project 2011 report for three case studies. It is observed from the three cases that each level of data fusion has its unique advantage. The power of pixel level fusion lies in its ability to provide an overview of bridge deck deterioration in one map as it appears in the fused image. On the other hand, feature fusion works better when only specific types of defects such as corrosion, delamination, and deterioration captured from inspection carried out by each of technologies referred to above. The proposed method is tested against filed inspection methods and core sample results described in the three case studies. The main findings of this research recommend utilizing data fusion in two levels as a new method to facilitate and enhance the confidence and capabilities of inspectors in interpretation of the NDE test results.

Porosity evaluation of in-service thermal barrier coated turbine blades using a microwave nondestructive technique

Porosity inspection of composite materials, ceramics and polymers is an important practical consideration in the nondestructive evaluation/testing (NDE/T) industry. The porosity of ceramics such as yttria stabilized zirconia (YSZ), the most widely used thermal barrier coating (TBC), for hot section metal components in a gas turbine is highly correlated with the thermal conductivity performance of the component. In-situ porosity inspection of TBCs after cyclic service is crucial to ensure the operational quality of TBCs and avoid any catastrophic system failure. The ability of microwave signals to propagate through a dielectric material and interact with the underlying surface and intrinsic properties, combined with the availability of high-resolution portable measurement equipment, make microwave imaging an attractive candidate for in-situ porosity inspection. In this paper, an extensive analysis of the simulation and measurement using a X-band open-ended rectangular waveguide (OERW) energy launch to evaluate the porosity of the TBCs of turbine blades is given. Existing mixing models are verified using simulation to determine the porosity and its relation to dielectric properties. The results show that the OERW microwave NDT/E technique can be used to characterize the porosity of TBCs, after cyclic services, using the phase of the reflection coefficient, S11. The results are validated using waveguide dielectric property measurements and image analysis produced using a scanning electron microscope (SEM).

A Study on Metallographic Microstructure of Steel Materials Subjected to Fire

In view of the fact that construction of modern buildings tends to use a high ratio of iron materials, this study aimed to obtain the ratio of components of steel’s microstructure under different test conditions by heating a A36 steel sheet commonly used in buildings, and applying metallographic replication testing. When the steel sheet was heated above 800°C and then rapidly cooled by water, the ratio of components of the structure were changed dramatically: components such as pearlite disappeared, ferrite was reduced from 90% to a low of 20%, bainite was increased to a maximum of 35%, and martensite was increased to a maximum of 45%. Since the substantial increase of martensite phase in this study led the microstructure of iron material to become thinned out and scattered, the ductility of such material was significantly reduced accordingly, thereby making the steel sheet easily broken. This study expected to provide the test findings of the mechanical behavior and metallographic structure of steel, after being heated to a high temperature and then naturally cooled, to other relevant units of construction engineering to serve as reference for their evaluation of non-destructive testing of steel structures.

Improved Ultrasonic Computerized Tomography Method for STS (Steel Tube Slab) Structure Based on Compressive Sampling Algorithm

This paper developed a new ultrasonic computerized tomography (CT) method for damage inspections of a steel tube slab (STS) structure based on compressive sampling (CS). CS is a mathematic theory providing an approximate recovery for a sparse signal with minimal reconstruction error from under-sampled measurements. Considering the natural sparsity of the damage, CS algorithm is employed to image the defect in the concrete-filled steel tube of Shenyang Metro line 9 for reducing the work time. Thus, in the measurement stage, far fewer ultrasonic measurement paths were selected from the dense net of conventional ultrasonic CT techniques to capture the underlying damage information. Then, in the imaging stage, ℓ1-norm minimization algorithm of CS theory is selected to recover the internal damage via fusing measurement data and solving optimization problem. The functionality of the proposed method is validated by three numerical concrete tube models with various conditions. Additionally, both the conventional ultrasonic CT technique and the proposed one are employed for ultrasonic inspection of the STS structure in Shenyang Metro line 9. Both the numerical and experimental results indicate that the proposed ultrasonic CT improved by CS has a great potential for damage detection, which provides an alternative accurate and effective way for non-destructive testing/evaluation (NDT/E).

An overview on how failure analysis contributes to flight safety in the Portuguese Air Force

Abstract Failure analysis has been, throughout the years, a fundamental tool used in the aerospace sector, supporting assessments performed by sustainment and design engineers mainly related to failure modes and material suitability. The predicted service life of aircrafts often exceeds 40 years, and the design assured life rarely accounts for all in service loads and in service environmental menaces that aging aircrafts must deal with throughout their service lives. From the most conservative safe-life conceptual design approaches to the most recent on-condition based design approaches, assessing the condition and predicting the failure modes of components and materials are essential for the development of adequate preventive and corrective maintenance actions as well as for the accomplishment and optimization of scheduled maintenance programs of aircrafts. Moreover, as the operational conditions of aircrafts may vary significantly from operator to operator (especially in military aircraft), it is necessary to access if the defined maintenance programs are adequate to guarantee the continuous reliability and safe usage of the aircrafts, preventing catastrophic failures which bear significant maintenance and repair costs, and that may lead to the loss of human lives. Thus being, failure analysis and material investigations performed as part of aircraft accidents and incidents investigations arise as powerful tools of the utmost importance for safety assurance and cost reduction within the aeronautical and aerospace sectors. The Portuguese Air Force (PRTAF) has operated different aircrafts throughout its long existence, and in some cases, has operated a particular type of aircraft for more than 30 years, gathering a great amount of expertise in: assessing failure modes of the aircrafts materials; conducting aircrafts accidents and incidents investigations (sometimes with the participation of the aircraft manufacturers and/or other operators); and in the development of design and repair solutions for in-service related problems. This paper addresses several studies to support the thesis that failure analysis plays a key role in flight safety improvement within the PRTAF. It presents a short summary of developed analysis and studies using optic and electronic (MEV) microscopy, material chemical composition analysis and Non Destructive Testing (NDT) to solve problems related to operation, maintenance and design issues. Additionally, it presents the investment that has been made by the Portuguese Air Force in the last two decades, to increase the flight safety through the implementation of powerful aircraft configuration management tools, and structural condition assessment methodologies based on strain measurements, NDT evaluation programs and, more recently, on Structural Health Monitoring systems in their fleets.

Dynamic Modulus of Three-Layer Boards with Different Furnish and Shelling Ratio

ABSTRACT This aims of this study were to investigate the relationship between non-destructive evaluation (NDE) and actual bending properties of particleboard, and to predict the bending properties of three-layer particleboard. Three kinds of raw materials, i.e. Hinoki (Chamaecyparis obtusa Endl.) strand, knife-milled Douglas-fir (Pseudotsuga manziesii (Mirb) Franco), and hammer-milled matoa (Pometia spp.) obtained from wooden industry, were utilized as furnish for experimental panel with methylene diphenyl diisocyanate (MDI) resin as binder. The NDE test was conducted by hit sounds using an FFT analyzer according to the spectrum peak ofwave frequency, while the static bending test was conducted according to JIS A-5908. The results reveal thatthe dynamic Young’s modulus as an NDE test has a potential for being used to predict the elastic bending of particleboards by a specific equation for adjusting its proper values. The values of NDE and static test aresignificantly different with a deviation range at 3-20%. The bending stiffness of three-layer particleboards manufactured from different wood species is predictable by observing the bending stiffness of two elements based on the thickness of its layers. The predicted values of bending stiffness and static test are significantly different with a deviation range at 5-24%. Keywords : dynamic modulus, three-layer boards, furnish, shelling ratio, predicted bending