Non-destructive Testing Techniques Research Articles

FFRC and SASW nondestructive evaluation of concrete strength from early ages

Free-Free Resonant Column and Spectral Analysis of Surface Waves are two nondestructive testing techniques which are becoming increasingly relevant in construction engineering, as they offer the possibility of assessing the mechanical properties of the building materials without damaging the sample. In the present study, these two testing methods are applied on concrete samples with increasing curing times, from 9 h to 60 days, estimating the dynamic elastic modulus and proposing relationships to obtain the compressive strength from these values. The nondestructive results are compared with the actual strength of the material obtained via uniaxial compression tests, proving the accuracy of the proposed nondestructive testing methodologies, even for early ages. SASW tests are also carried out on a reinforced concrete sample, concluding that the presence of the reinforcement does not alter the results of the test.

Research on detection method of concrete compressive strength based on dielectric properties

Compressive strength of concrete structures is a crucial quality parameter that determines their performance throughout lifespan. This study introduces an innovative approach of utilizing electromagnetic nondestructive testing to assess the compressive strength of mature concrete. The dielectric constant and compressive strength of standard specimens were tested by open coaxial probe and pressure testing machine, respectively, using ordinary Portland cement concrete with various water-cement ratios (0.4, 0.45, 0.5, 0.55, 0.6 and 0.65) as the research object. It has been discovered that increasing porosity reduces the number of polarized particles per unit volume of concrete, resulting in a decrease in polarization intensity. This decrease is manifested as a reduction in the dielectric constant in macro parameters. The relationship between porosity and dielectric constant was characterized using a series-parallel composite concrete dielectric model. Additionally, as porosity increases, the compressive strength of concrete decreases exponentially. By considering porosity as an intermediate variable, a concrete compressive strength model based on the dielectric constant was established. The model exhibits an average error of 3.62%, indicating the precise characterization of concrete's compressive strength using the dielectric constant. This model can serve as a theoretical basis for the implementation of electromagnetic nondestructive testing techniques in strength evaluation.

Characterization of a leaky earth dam using integrated geophysical surveys

Early earth dams were mainly constructed using a soil core wall, which is susceptible to a variety of potential risks such as inhomogeneity, poor compactness, and leakage due to multiple fillings and biological damage. To ensure safe operation of the dam, cost-effective geophysical non-destructive testing techniques should be considered during routine maintenance. This paper presents a case study of an earth dam designed for water storage and flood control that experienced a leak problem. To provide a basis for future leakage control, we carried out 2D integrated geophysical surveys utilizing Electric Resistivity Tomography (ERT), Ground Penetrating Radar (GPR), and Surface Wave (SW) methods along the dam axis. In conjunction with the fast attenuation characteristic of GPR signals, the low resistivity anomalies recovered by the ERT provide evidence to reveal the leakage area within the dam structure. Moreover, the shear wave velocity variation retrieved by the SW method helps to determine the distribution of bedrock and soil layers. By integrating the results mentioned above, the interpretation outcome yields a comprehensive understanding of the internal condition of the earth dam. The successful investigation of the dam structure and the mapping of the leakage area demonstrate the effectiveness of integrated geophysical surveys in characterizing earth dams. It also suggests that it is essential to consider the difference between various geophysical results and the underlying reason when integrating them to characterize leaky earth dams.

Improving efficiency of local wavenumber estimation for damage detection in thin-walled structures

Full-field imaging of guided ultrasonic waves is an emerging Nondestructive Testing (NDT) technique for the inspection of thin-walled structures. One of the most effective full-field processing techniques is the Local Wavenumber Estimation (LWE) which can be applied to detect various types of damage in both homogeneous and multilayer specimens. In this paper, we discuss the possibilities for optimizing the efficiency of the LWE algorithm to facilitate its practical applications. We propose several different signal processing approaches to optimize the algorithm's computational efficiency without sacrificing the damage imaging quality. We evaluate the influence of these improvements by measuring the computation time necessary to perform particular processing steps of the LWE process. We also provide the implementation guidelines for the proposed optimization techniques. The proposed improvements allow for a considerable reduction in the processing time of the LWE with respect to the baseline implementation of the algorithm, ranging from a factor of 10 to a factor of 24, depending on the input dataset.

RCF crack direction assessment in moving ferromagnetic material by DC electromagnetic NDT technique

The rolling contact fatigue (RCF) cracks that initiate from the surface of ferromagnetic materials in aviation bearings and high-speed rails are typically inclined at varying angles, posing a serious threat to safety. Therefore, a rapid and quantitative characterization of inclined cracks is of great importance. This paper investigates the distribution of magnetic fields and motion-induced eddy current (MIEC) in direct current (DC) electromagnetic non-destructive testing (NDT), and proposes an approach for measuring the direction of RCF cracks in moving ferromagnetic materials. The magnetic field and MIEC distributions in the moving ferromagnetic material are initially investigated, followed by a numerical simulation exploring the impact of crack inclination angle and depth on detection signals. The resulting relationship between crack propagation angle, depth, and detection signal is then obtained. Furthermore, a DC electromagnetic NDT platform has been designed and a quantitative detection approach for inclined cracks has been proposed and validated through experiments. Finally, a real scenario detection is carried out. The investigation presented in this paper demonstrates that the DC electromagnetic NDT technique is applicable not only for assessment RCF crack direction in moving ferromagnetic materials, such as rotating aviation bearings, but also for characterizing inclined cracks under conditions of fast relative motion between the probe and the ferromagnetic material (e.g., high-speed rail, pipeline, etc.).

Condition & Life Evaluation of Structure by Various NDT Techniques for Reuse

The most crucial element to take into account when developing operations in the building sector is steel. Therefore, it is essential to assess the state of steel in real-time to prevent failure later on in the structure’s useful life. When a structure’s strength declines over time, structural issues such as overloading, material deterioration, and physical damage may be discovered. If these issues are not addressed, the structure’s estimated lifespan may be shortened. For the purpose of evaluating the physical state of all structures that are 15 to 30 years old, the Indian government authorized a structural audit. The non-destructive testing techniques are adopted while conducting a structural audit on a steel structure. such as Vernier Thickness Caliper Test, Dye-Penetration Test, Ultrasonic Thickness Gauge, and Visual Inspection. The carbonation of concrete is one of the main reasons for the corrosion of reinforcement. The carbonation and corrosion deterioration model is developed and the Life Evaluation of Structure is showcased in this paper. The Sangam Steel Plant in Wardha, Maharashtra, undergoes a structural audit to determine the steel structure’s physical condition and determine the most cost-effective rehabilitation options to extend the structure’s life.

Evaluation of material surface properties using one-way collinear mixing Rayleigh waves

Nonlinear Rayleigh waves are useful for material surface damage detection. Traditional non-destructive testing (NDT) techniques based on higher harmonics of Rayleigh waves are inevitably interfered with by the nonlinearity of measurement systems. To overcome this disadvantage, an approach based on one-way collinear mixing Rayleigh waves (MRWs) is proposed to evaluate the material surface properties. A wedge with two different incidence angles for the excitations of transverse and longitudinal waves is designed to generate one-way collinear MRWs. The one-way collinear MRWs can be generated on the whole surface of the material, and propagate along the propagation way under one excitation. Numerical simulations of one-way collinear MRWs under different surface properties, which are characterized using different third-order elastic constants, are studied on a semi-infinite aluminum. Experiments are also conducted on the aluminum specimen, whose surface is corroded by hydrochloric acid so as to change the material surface properties. Both numerical and experimental results show that the one-way collinear MRWs are generated effectively, and the defined relative acoustic nonlinearity parameter increases with the propagation distance as well as the severity of the material surface damages. The results verify the effectiveness of the proposed MRW-based method and prove that it would be a promising NDT technique for the accurate evaluation of material surface properties.

Research on the surface crack detection of specimen manufactured by selective laser melting based on local singular value decomposition method

SLM (selective laser melting) is an important additive manufacturing technology. Parts with complex structures can be produced by SLM, so surface cracks and other defects within SLM parts are difficult to be identified by traditional nondestructive testing techniques. In this paper, laser ultrasonic technology is proposed to identify the surface crack of SLM specimen. Because of the anisotropy and residual stress of the specimen, the time signal is strongly interfered with by noise, which makes the identification and location of the crack difficult. To solve this problem, the phase space was reconstructed from the time signal and analyzed by the local singular value decomposition method. According to the result of the experiment, this method can reveal the variation of the phase space and has a good effect on the identification and location of the surface crack whose depth is larger than 1 mm.

Research on non-destructive testing of stress in ferromagnetic components based on metal magnetic memory and the Barkhausen effect

In this paper, the relationship between the effective field of metal magnetic memory (MMM) emission and the structural stress of the ferromagnetic components is studied. The relationship between the voltage of the received magnetic Barkhausen noise (MBN) and the excitation source is also studied. Moreover, the characteristics of the emission spectrum of the MMM and MBN detection signals, and the influences of the lift-off distance on the stress detection accuracy of the two detection methods are studied. The advantages and disadvantages of the two magnetic non-destructive testing (NDT) techniques are analyzed separately, and their functions are combined to enhance the advantages and weaken the disadvantages. Modern signal analysis methods such as wavelet packet transform and signal feature extraction are introduced to process MMM signals, and a classifier for stress grading is established in combination with machine learning methods. On this basis, graded detection of the temperature stress of the continuous welded rail (CWR) was carried out. The detection accuracies of the 30–50 MPa, 50–70 MPa and 70–90 MPa stress grade ranges of CWR reach 71.43%, 82.76% and 75.00% respectively. The rapid grading detection of the temperature stress of the CWR and the rapid judgment of the structural stability of the CWR are realized based on the MBN-MMM detection technique.

Mode purification for multimode Lamb waves by shunted piezoelectric unimorph array

Guided wave-based nondestructive testing and structural health monitoring methods have been developed to exhibit attractive potentials and best prospects for rapid and sensitive detection of defects or damage in engineering structures. Different modes of guided waves can provide different sensitivities of damage detection. However, the multimode and mode conversion nature of guided waves poses significant challenges to mode purification of received signals. This study aims to design a metamaterial-based smart transducer for mode purification of Lamb waves in a plate, which can filter out an undesired mode of the Lamb wave to enhance sensing and actuating signals of a dominated mode. The smart transducer consists of a periodic array of shunted piezoelectric unimorphs with staggered polarization directions and is bonded on the surface of a host plate. Numerical and experimental results show that a local resonance bandgap for an anti-symmetric Lamb wave, rather than a symmetric Lamb wave, can be obtained and tuned through the shunting inductance circuit. Within such mode bandgap, the wave control for propagating a specific mode of the Lamb wave can be further realized, i.e., the mode of the Lamb wave is purified. The design presented herein offers enhanced capabilities in controlling guided wave propagation for engineering applications and nondestructive testing techniques.

The novel procedure of active thermal ndt: combining heating and forced cooling

A novel technique of active thermal nondestructive testing is proposed. It involves consecutive heating and forced cooling of the surface of test objects. The results of numerical modeling and experiments have demonstrated efficiency of this technique in case of test materials, which are characterized by a high level of emission/absorption noise. Optimization of such test procedure requires correctly choosing power and turn-on time of forced cooling to stimulate increase of temperature contrast over defects at particular times. An additional advantage of forced cooling is decrease of a thermal load on test materials that may be important in case of composites.

Development of a novel real-time AE source localisation technique using ANN for health monitoring of rail section: an experimental study

Almost all countries are using railways to transport passengers and freight. Due to heavy load and environmental exposure, these rail sections are prone to damage. Thus, structural health monitoring of the rail section is an essential topic of research to ensure safety and predict the remaining useful life of the track. Consequently, the detection and localisation of damages/cracks in rail section are crucial. It also helps in taking corrective action in time. In this context, the acoustic emission (AE) technique is found to be a powerful non-destructive testing technique which has great potential to localise cracks in rail sections. Actually, the initiation or growth of a damage/crack in a structure emits AE waves, which may be captured using AE sensors mounted on different locations of the structure. The damage itself acts as an AE source. Subsequently, in this study, a novel approach is developed to localise the AE source in a rail section using the artificial neural network (ANN). The ANN model is based on the experimental crack signals captured through a single AE sensor by placing it at different regions of the rail section. For each position of the sensor, cracks are simulated using pencil lead break at different locations along the length and depth of the rail section. It is observed that the developed ANN model predicts the location of the AE source with better accuracy in comparison to the existing localisation methods. The minimum error is found to be less than 1%. Therefore, it can be concluded that the developed ANN model is a suitable option for predicting potential crack locations during real-time monitoring of rail sections.

Quantification of hidden corrosion in aircraft structures using enhanced D-Sight NDT technique

In this paper, the enhancement of the D-Sight non-destructive testing technique was proposed by enriching it with a possibility of quantification of hidden corrosion typical for metallic fuselages of aircrafts. The proposed approach is based on the developed image processing technique, which allows the quantifying of the spatial dimensions of a corroded area from D-Sight images, which is supported with finite element modeling to achieve information about the depth and degree of corrosion of a given structure. The D-Sight inspections were validated using metrological measurements and the digital image correlation technique to introduce correction factors for the evaluations of dimensions of a corroded area using D-Sight due to overestimations typical of this technique. The performed studies allowed determination of a lower bound of the detectability of hidden corrosion using the D-Sight technique. The proposed enhancements will improve inspections of aircraft structures, where hidden corrosion remains a serious and unsolved problem.

Deep Autoencoder Thermography for Defect Detection of Carbon Fiber Composites

Infrared thermography (IRT) is an economical nondestructive testing technique for structural health monitoring of composite materials. However, the nonlinear nature of the thermographic data and the adverse effects of noise and inhomogeneous backgrounds prevent it from achieving satisfactory results. Most of the existing thermographc data analysis methods are supervised and/or linear, which therefore are not favorable for nonlinear feature extraction of unlabeled thermograms. In this work, a deep autoencoder thermography (DAT) method is proposed for detecting subsurface defects in composite materials. The multi-layer network structure of DAT can handle nonlinear temperature profiles, and the output of the intermediate hidden layer is visualized to highlight defects. The layer-by-layer feature visualization reveals how the model extracts defect features. A loss inflection point scheme is utilized to determine a suitable depth of the model. Moreover, a new quantitative index is proposed to compare the defect detectability of different methods.

Raman Spectroscopy for Non-Destructive Detection of Pesticide on Guava Peel

Pesticides are one of the substances that are widely used to protect plants from pests and plant diseases, and their use must be controlled for the public health. Currently, the pesticide contamination is determined by chromatographic, but this technique is destructive and not easy to implement. Therefore, this research is proposed to overcome these problems. Raman scattering technique as a non-destructive testing technique and easy to implement is used in this research. This technique utilizes Raman scattering resulting from laser excitation in a sample. Pesticide detection was carried out by observing the difference in Raman shift wavelength between samples containing pesticides and samples that did not contain pesticides. The experiments were done on guava peels with coated pesticide delthametrin 25 g/l. By excitation with laser wavelengths 532 nm and 785 nm, the differences in Raman shifts at wavelengths 1,225 nm and 1,480 for samples coated pesticide, and Raman shifts at wavelengths 1,008 nm and 1,480 nm for samples which is treated are obtained, respectively. From this research, it can be concluded that Raman scattering technique can be used as non-destructive and easy technique for detection pesticide contamination.

Prognostic Health Management Using IR Thermography: The Case of a Digital Twin of a NiTi Endodontic File.

Prognostic and health management technologies are increasingly important in many fields where reducing maintenance costs is critical. Non-destructive testing techniques and the Internet of Things (IoT) can help create accurate, two-sided digital models of specific monitored objects, enabling predictive analysis and avoiding risky situations. This study focuses on a particular application: monitoring an endodontic file during operation to develop a strategy to prevent breakage. To this end, the authors propose an innovative, non-invasive technique for early fault detection based on digital twins and infrared thermography measurements. They developed a digital twin of a NiTi alloy endodontic file that receives measurement data from the real world and generates the expected thermal map of the object under working conditions. By comparing this virtual image with the real one acquired by an IR camera, the authors were able to identify an anomalous trend and avoid breakage. The technique was calibrated and validated using both a professional IR camera and an innovative low-cost IR scanner previously developed by the authors. By using both devices, they could identify a critical condition at least 11 s before the file broke.

Damage detection in composites using non-destructive testing aided by ANN technique: A review

Damages are inevitable in structures and effective damage detection techniques are important for maintaining their health. Many weight-sensitive engineering applications use composite materials, especially fiber-reinforced laminates. Common damages of these materials include delamination, fiber breakage, fiber pull-out, etc. Various non-destructive testing (NDT) techniques are reported in the literature for damage detection in composites, such as ultrasonic testing, vibration-based techniques, acoustic emission technique, optical NDT and imagining techniques. However, due to the complex properties of composite materials, conventional techniques for analyzing NDT data are difficult to implement. In this context, artificial neural network (ANN) technique is a promising alternative for analyzing NDT data for damage detection. In this study, an attempt is made to explore the state-of-the-art of damage detection in composites using NDT aided by ANN. The work discusses the pros and cons of different methods and is expected to help in identifying the appropriate method for damage detection in composites.

Perspective on pulse compression favorable infrared imaging techniques for non-destructive testing and evaluation of solids

Abstract Inspection reliability of sub-surface defects is imperative for safer functionality of critical components/materials/structures used in a wide variety of applications in various industries. The need for reliable, fast, remote, safe inspection and evaluation methods for detection of hidden defects increases in parallel with the demand for more sustainable solutions which helps in inherent modifications in design and manufacturing specifications. During in-service operation, the hidden defects are typically originated from various loading conditions leading to catastrophic failure. This perspective explores the best possible reliable, fast, remote, safe, and easy to implement for field inspection and evaluation experimental method and the associated post-processing approach using InfraRed Imaging (IRI) for Thermal Non-Destructive Testing and Evaluation (TNDT&E) of Glass Fibre Reinforced Polymer (GFRP) materials having delamination defects. This perspective further explores the state-of-the-art infrared imaging modalities used in TNDT&E by highlighting their advantages and limitations in terms of the detection sensitivity and depth resolvability to detect the subsurface defects located at interior of material. Most of the proposed experimental and post-processing techniques presented in the literature for TNDT&E, explore the observed spatial thermal contrast over the defective region of sample to provide the depth resolvability from the reconstructed thermograms even though it is obtained from the temporal data processing on the captured image sequence. This perspective provides an insight on the state-of-the-art research in the field of thermal/infrared non-destructive testing and evaluation and associated post-processing approaches to visualize the hidden subsurface defects not only resolved by spatial thermal gradients but also simultaneously provide temporal thermal gradients to locate defective regions.

Mapping internal strain fields of fused filament fabrication metal filled polylactic acid structure using digital volume correlation.

With the advancement in Fused Filament Fabrication (FFF), its application is increasing widely across different industries such as aeronautical, biomedical, robotics, etc. The internal structure is becoming more complex and intricate with varying materials of reinforcement which are used to improve mechanical properties. Current measurement techniques like Digital Image Correlation (DIC) are non-destructive testing methods that do not provide enough information on the behaviour of internal microstructure for anisotropic FFF materials. Digital Volume Correlation (DVC) is non-destructive testing technique which provides full field internal 3D deformation and strain fields. Copper particle filled PLA samples manufactured using FFF method with 20, 40, 60 and 80 infill percentages were loaded in tension inside Micro-CT. X-rays were passed through the sample to get a volumetric dataset for different loadings. Using DVC method on the dataset, internal displacement and strain fields were generated for 20, 40, 60 and 80 infill percentage FFF sample.

Focusing higher-order Lamb waves based on the Luneburg lens

In order to improve the spatial resolution and the signal-to-noise ratio of Lamb waves in structural health monitoring systems or non-destructive testing techniques, this study presents the construction of Luneburg lenses for focusing higher-order Lamb waves based on the thickness variation. The dispersion curves of Lamb waves are calculated firstly, from which the relation between the phase velocity of a specific mode and the plate thickness is quantified. After that, the plate thickness is determined via the refractive index variation. To demonstrate the generality of this design scheme, two lenses, i.e., the A1-wave-based Luneburg lens and the S2-wave-based Luneburg lens are constructed, and their focusing abilities are examined via numerical simulations in both the time domain and frequency domain. It is revealed that the A1 wave and S2 wave can be focused with a focusing size smaller than one wavelength. The design methodology is easy to realize and can be used to control higher-order Lamb waves efficiently, which also provides potential application values in wave detections and energy collections.