Nondestructive Evaluation Techniques Research Articles

Terahertz Nondestructive Stratigraphic Analysis of Complex Layered Structures: Reconstruction Techniques

Terahertz (THz) time-of-flight tomography (TOFT), a nondestructive-evaluation technique for the stratigraphic characterization of structures with layers on the micron-to-millimeter scales, has proven to be challenging to apply to samples containing both micron-scale and millimeter-scale layers. In THz TOFT, echoes reflected from distant interfaces and defects are often obscured as they may be immersed in a noisy background as such features in the reflected signal may be weak due to attenuation and dispersion, leading to the loss of valuable information. Moreover, overlapping echoes from any optically thin layers, such as thin coatings on thick specimens, are likely to be mistaken for a single interface in reconstructing the stratigraphy. Thus, layered structures containing both thick and thin layers have proven problematic for THz TOFT characterization. In this paper, a sparse-deconvolution (SD) technique, based on an interior-point method, and including a propagation model accounting for dispersion is demonstrated. The method is shown to be successful in extracting the impulse response of samples that combine the challenges of both thick and thin layers. The robustness and effectiveness of this method are verified numerically and experimentally. While the proposed SD approach does not perform as well as cross-correlation (CC) techniques in terms of the maximum thickness, it can provide a clearer and more accurate reconstruction of moderately thick samples incorporating thin layers.

Experimental Evaluation of Miniature Impedance Board for Loosening Monitoring of the Threaded Pipe Connection

Electromechanical impedance (Electromechanical impedance)-based methods as potential nondestructive evaluation (NDT) techniques have been widely used in the field of structural health monitoring (SHM), especially for the civil, mechanical, and aerospace engineering fields. However, it is still difficult to apply in practical applications due to the limitations of the impedance measurement hardware, which is usually expensive, bulky, and heavy. In this paper, a small, lightweight, and low power consumption EMI-based structural health monitoring system combined with the low-cost miniature impedance board AD5933 was studied experimentally to investigate its quantifiable performance in impedance measurement and structural damage identification. At first, a simple impedance test with a free PZT patch was introduced to present the impedance calibration and measurement procedure of AD5933, and then its calibration performance was validated by comparing the signature with the one measured by a professional impedance analyzer (WK6500B). In order to further validate the feasibility and effectiveness of the AD5933 board in practical applications, a threaded pipe connection specimen was assembled in the laboratory and then connected with the AD5933 to acquire its impedance signatures under different loosening severities. The final results demonstrated that the impedance measured by the AD5933 show a good consistency with the measurements by the WK6500B, and the evaluation board could be successfully utilized for the loosening severities identification and quantitatively evaluation.

Time of flight diffraction for rough planar defects

Ultrasonic non-destructive evaluation techniques, such as time-of-flight diffraction (ToFD) for which the arrival times of waves diffracted from crack tips are analysed to locate and size defects, are well understood for smooth defects. In environments where extreme changes in temperature and pressure occur, the damage that may arise is often non-uniform and more difficult to characterise when designing and qualifying an inspection. This article investigates the implementation of ToFD methods for sizing rough defects using a purely theoretical approach. High-fidelity finite element modelling and stochastic Monte Carlo methods are used to provide physical and statistical insights for the dependence on both incident beam angle and degree of roughness for the case of planar defects. Optimal incident angles for ultrasonic ToFD techniques were determined in the 1980s but largely based on theoretical and experimental investigations for smooth defects. However, rough defects produce tip-diffracted signatures that are more complicated than for their smooth counterparts, largely due to multiple scattering effects related to mode conversion and propagation of surface waves along the rough surface. It is shown that roughness may cause larger diffraction amplitude values at different angles, which leads to increased uncertainty when sizing, with illustrative examples and physical interpretations provided. Comparisons of amplitudes for smooth and rough defects of the same size are also demonstrated. The ToFD method, using envelope peak detection and autocorrelation approaches, is implemented to estimate the size of rough cracks, and the effects of roughness on the accuracy of this sizing are investigated with statistical analysis.

A Combined Inductive and Capacitive Non-Destructive Evaluation Technique Using a Single Spiral Coil Sensor

“Insulator-conductor” hybrid structures, such as insulated pipe/vessel and metallic structures with composite repairs, have been widely used in industry in recent years. Due to the two distinct types of materials, the comprehensive Non-destructive Evaluation (NDE) of such hybrid structure is often achieved via complementary NDE techniques, which may cause efficiency and cost issues, i.e., the conducting layer is inspected by magnetic induction related technique and the insulation layer is inspected by capacitive technique. This paper proposes a combined inductive and capacitive non-destructive evaluation technique using sensor with a single spiral coil etched on a Printed Circuit Board (PCB). The proposed technique uses both the inductance and stray capacitance of the planar coil. By measuring the coil impedance at frequencies below and above the resonant frequency, the inductive and capacitive responses can be separated to some extent, offering a simple and efficient way to image and discriminate the defects in both layers of the hybrid. Equivalent circuit analysis, Finite Element simulations and experimental research are applied. A system to implement this technique has been constructed, and its feasibility in imaging defects in insulators, conductors and a hybrid structure has been verified. The developed system successfully detected surface and hidden slots in Perspex, a through hole in aluminium, and a surface crack in steel at various lift-offs (up to 7 mm). In addition, line scan results on a steel plate with a surface crack covered by a Glass-fibre Reinforce Plastic (GFRP) plate with a hidden flat-bottomed circular hole are presented and discussed to further demonstrate the feasibility of the proposed technique on the defect detection and discrimination for “insulator- conductor” hybrid structures.

Numerical evaluation of a muon tomography system for imaging defects in concrete structures

Among numerous applications of muon tomography, deployment in civil structures has caught attraction of many recently. In this work, the appropriateness of muon scattering tomography to detect defects in concrete structures has been studied numerically. A few basic concrete structures that are frequently used in civil construction have been considered as test cases. A simulation has been performed on Geant4 platform where an imaging setup built with several layers of gaseous ionization detectors, having a specific spatial resolution for tracking the muons, has been modeled. The images of the test cases with and without the defect have been simulated for variable exposure of cosmic muons on the basis of their scattering from the composite concrete structures. The images have been compared using t-test to evaluate the performance of the imaging setup in identifying the defects. Further processing of the images has been done with a pattern recognition method proposed in our earlier work to examine the credibility of the method of defect identification in civil works. The efficacy of the said method has been evaluated in terms of the PRM-score devised in this work. The limitation and advantages of the present application of the muon scattering tomography encompassing the imaging and image processing technique in nondestructive evaluation of concrete structures have been discussed.

Dual-mode Non-Destructive Evaluation Technique Using a Single Spiral Coil

This paper proposes a combined inductive and capacitive non-destructive evaluation technique using a single spiral coil on a Printed Circuit Board (PCB). By measuring the coil impedance at frequencies below and above the resonant frequency, the inductive and capacitive responses can be separated to some extent. Equivalent circuit analysis, Finite Element simulations and experimental research are applied. A system to implement this technique has been constructed, and its feasibility in imaging defects in insulators, conductors and a hybrid structure has been verified.

A Compact Laser Shearography System for On-Site Robotic Inspection of Wind Turbine Blades

Shearography is an optical technique in the field of non-destructive evaluation (NDE) of various materials. Its main advantages are that it is non-contact type and can cover a large area in a single inspection. As a result, although it has been widely acknowledged as an effective technique particularly for NDE of composite materials to detect subsurface defects such as delamination, disbond, cracks and impact damages, the use of shearography for on-site inspection of wind turbine blades (WTBs) has not been reported. This is due to wind causing structural vibration in the WTB. The solution in this paper is to make the shearography sit on the WTB during inspection when the WTB is parked, so that the relative motion between the shearography and the WTB is minimized within the tolerance of the shearography system. The ultimate goal of the solution is to enable a robot assisted shearography system to inspect the WTB on-site. This paper presents the research work on a new shearography design for integration with a robotic climber for on-site WTB inspection. The approach is tested and evaluated in experimental settings, and comparative assessment of the approach with other robotic NDE techniques is carried out. The results demonstrate the potential benefits and suitability of the approach for on-site robotic inspection of WTBs.

An experimental investigation on damage mechanisms of thick hybrid composite structures under flexural loading using multi-instrument measurements

In this study, damage characterization of thick carbon/glass fiber reinforced hybrid composites is performed under flexural loading conditions via two non-destructive evaluation (NDE) techniques, i.e., digital image correlation (DIC) and acoustic emission (AE). Experimental results demonstrate that the flexural modulus of the hybrid composites is strongly correlated with the location of carbon fiber plies; the closer these plies are to the laminate faces, the higher is the modulus. On the other hand, the flexural strength depends on the type and extent of damage initiation in the laminates. Interply hybridization of carbon fiber reinforced composites (CFRPs) with glass fiber not only improves their flexural strength and failure strain but also facilitates failure predictability in CFRPs. The transverse and shear strains associated with various failure modes in thick hybrid laminates are efficiently captured by the DIC technique. In addition, AE results reveal that the strain levels associated with the onset of acoustic activity are linked to failure in the carbon fiber plies of the hybrid laminates. Furthermore, these observations made by DIC and AE on thick hybrid laminates are confirmed with optical fractography. Finally, it is revealed that ply lay-up sequence and laminate thickness notably alter both the mechanical performance and damage mechanisms of hybrid composites.

Optimising sensor pitch for magnetic flux leakage imaging systems

Sensor arrays can significantly increase the speed at which inspections and subsequent imaging of flaws is performed[1]. This work focuses on developing a software approach for optimising the spacing between quantum well Hall-effect (QWHE) magnetic sensors used for magnetic flux leakage (MFL) imaging, where this approach could be adapted for any non-destructive evaluation (NDE) technique in which imaging is obtained. A ground mild steel weld sample containing two surface-breaking flaws prepared by Sonaspection was scanned using an XYZ MFL imaging system developed at the University of Manchester[2,3,13,14]. The scan was taken with an autonomously controlled lift-off height of 0.75 mm, with an x-y measurement step of 100 μm and an applied magnetic field of 30 mT root mean square (RMS) at a frequency of 400 Hz. This data (ie magnetic image) was then processed to simulate different measurement step sizes, to determine any relationship between step size and flaw detectability (flaw signal to weld background response). This work effectively simulates different sensor pitches (separation between sensors) of integrated QWHE sensor arrays from 100 μm to 5 mm, with the goal of determining both the minimum number of sensors required in the array and the optimal spacing to maximise scan speeds and help determine optimum inspection parameters to develop the technology of low-power MFL imaging. This optimisation process could be applied to any NDE imaging system (electromagnetic or other) currently used, with results dependent on the inspection parameters.

A Review on Meat Quality Evaluation Methods Based on Non-Destructive Computer Vision and Artificial Intelligence Technologies

Increasing meat demand in terms of both quality and quantity in conjunction with feeding a growing population has resulted in regulatory agencies imposing stringent guidelines on meat quality and safety. Objective and accurate rapid non-destructive detection methods and evaluation techniques based on artificial intelligence have become the research hotspot in recent years and have been widely applied in the meat industry. Therefore, this review surveyed the key technologies of non-destructive detection for meat quality, mainly including ultrasonic technology, machine (computer) vision technology, near-infrared spectroscopy technology, hyperspectral technology, Raman spectra technology, and electronic nose/tongue. The technical characteristics and evaluation methods were compared and analyzed; the practical applications of non-destructive detection technologies in meat quality assessment were explored; and the current challenges and future research directions were discussed. The literature presented in this review clearly demonstrate that previous research on non-destructive technologies are of great significance to ensure consumers’ urgent demand for high-quality meat by promoting automatic, real-time inspection and quality control in meat production. In the near future, with ever-growing application requirements and research developments, it is a trend to integrate such systems to provide effective solutions for various grain quality evaluation applications.

A case study on deterioration assessment and rehabilitation of fire damaged reinforced concrete structure

Fire is one of the most severe hazards that building structures may experience during their lifetime. A fire spread to the whole structure can cause unexpected damages to the structural elements. Mainly, the building type is crucially important for the type and the level of damage to the building because of the fire. Post fire investigation of damaged structure is required to determine the extent of damage to concrete elements and to work out system of effective repair/rehabilitation measures to maintain the structural integrity of fire effected structural components. The paper covers in brief the strength and durability study on fire damaged building in Delhi, India. The study reports the extent of fire damage. Optical Microscopy (OM), X-Ray Diffraction (XRD) and Deferential Thermal Analysis (DTA) studies were carried out on the sample concrete cores extracted from different identified portions of the fire exposed concrete are highlighted in this paper. Extent of damage occurred in the Reinforced Cement Concrete (RCC) i.e. RCC columns/beams/slabs are described based on the detailed evaluation by various Non-Destructive Evaluation Techniques covering Cover study & Ultrasonic Pulse Velocity (UPV) testing. Repair and remedial measures required for restoration and strengthening of the fire affected RCC columns/beams/slabs using indigenously available repair materials and techniques are also highlighted in this paper.

A case study on deterioration assessment and rehabilitation of fire damaged reinforced concrete structure

Fire is one of the most severe hazards that building structures may experience during their lifetime. A fire spread to the whole structure can cause unexpected damages to the structural elements. Mainly, the building type is crucially important for the type and the level of damage to the building because of the fire. Post fire investigation of damaged structure is required to determine the extent of damage to concrete elements and to work out system of effective repair/rehabilitation measures to maintain the structural integrity of fire effected structural components. The paper covers in brief the strength and durability study on fire damaged building in Delhi, India. The study reports the extent of fire damage. Optical Microscopy (OM), X-Ray Diffraction (XRD) and Deferential Thermal Analysis (DTA) studies were carried out on the sample concrete cores extracted from different identified portions of the fire exposed concrete are highlighted in this paper. Extent of damage occurred in the Reinforced Cement Concrete (RCC) i.e. RCC columns/beams/slabs are described based on the detailed evaluation by various Non-Destructive Evaluation Techniques covering Cover study & Ultrasonic Pulse Velocity (UPV) testing. Repair and remedial measures required for restoration and strengthening of the fire affected RCC columns/beams/slabs using indigenously available repair materials and techniques are also highlighted in this paper.

Rapid Material Characterization using Smart Skin with functional Data Analysis

Automotive industries in the last decade are demanding for lightweight, corrosion resistance and improved fatigue performance materials. Composites having all such properties quickly gain popularity. Due to complex fabrication methods, composites are known for various process defects. Thus, monitoring and characterizing the composite component before assembly is necessary to maintain the overall structural integrity. Further a rapid and reliable inspection is much needed addition in most automotive industries to save time.
 Non-Destructive Evaluation (NDE) is popular for component testing in the automobile industry because they do not cause any permanent alteration to components. Some NDE techniques require sensors (Piezo Electric transducers, PVDF films, Optical fiber, etc.) that need to be bonded to the structure for testing. Some of these sensors are expensive and cannot be reused once detached. This work aims at the reusability of sensors. Further, the reusable sensors can be deployed in an array configuration for multi-purpose NDE. SMART Skin shall be explained as a Multiple-Transmitter-Multiple-Receiver (MTMR) Piezo-ceramic based sensor (PZT) array which is embedded to a conformable skin. The bottom layer of the skin is coated with pressure-sensitive adhesive to be attached to most curved and non-curved structural surfaces. Each PZT sensor nodes are individually controlled by a MATLAB code that actuates and receive the GW waves signals.
 In this work, we have validated the ability of rapid material characterization using isotropic materials.
 Using experimental data collected by the proposed methodology, we have developed an automated material classification algorithm using various machine learning algorithms. A novel application of functional data analysis (fDA) which converts discrete samples into continuous curves is used. The curves are represented as linear combinations of basis functions. The advantage of this fDA method is that we use the shape of the signal instead of extracting features from the signal. Several choices of basis coefficients such as fourier series, wavelet and B-spline are considered of which spline basis gives the best results. These basis coefficients are then feed into machine learning models like Support Vector Machine (SVM), Random Forest (RF), k nearest neighbor (knn) for classification. The efficacy of this novel method is compared with conventional feature extraction techniques such as zero-crossing coefficients, absolute maximum value, different statistical features like mean and variance, energy of the signal. Encouraging results are obtained that shows the fDA methodology is efficient over the conventional feature extraction methods as it improves the prediction performance on the classifier and result in a faster and cost-effective model by reducing the predictor dimensionality.

Ray tracing method for ultrasonic array imaging of CFRP corner part using homogenization method

A reliable nondestructive evaluation technique that can effectively detect and quantify the internal defects of corner parts in complex-shaped carbon fiber reinforced plastic (CFRP) structures is highly demanded for assuring safety and reliability of safety-critical structures. The conventional methods generally utilize normal incidence ultrasound and suffer from poor image quality due to the unfocused beam. To produce a fully focused image of the CFRP corner part, the delay-and-sum total focusing method (TFM) is preferred. The prerequisite for TFM imaging is to calculate ultrasonic ray paths, which is challenged by the curved shape, elastic anisotropy and multilayered microstructure. In this paper, the complex ultrasonic ray paths transmitting through the corner parts of CFRP structures from the concave side are calculated for ultrasonic array imaging. A ray theory-based homogenization method is firstly proposed to describe the wave velocity distribution of corner parts, which is critically important to the subsequent ray tracing calculation. A ray tracing method based on Dijkstra's algorithm is further developed for rapid calculation of multiple ray paths between two specified points when the ultrasound is incident from the corner's concave surface. To demonstrate the validity of ray tracing method, the TFM images of an CFRP corner part with side drilled holes (SDH) at different depths obtained using three different types of ray paths, are compared and analyzed. Results show that TFM images using ray paths with the minimum or maximum ultrasonic travel time present unsatisfactory image quality due to the obvious structural noises from ply reflections. In contrast, the signal to noise ratio of the image is significantly improved when TFM uses the ray paths with the weakest refraction, and all SDHs are detected and accurately positioned. This paper proves that the proposed ray tracing method is an effective method for imaging the corner parts of CFRP structures.

Tensile stress effect on crack depth quantification in ferromagnetic materials using ECPT

As one of the fast-developed NDT&E (nondestructive testing and evaluation) techniques, eddy current pulsed thermography (ECPT) is extensively used for crack detection and quantification in ferromagnetic pressure components. However, in the practical inspection, the stress has significant influences on the permeability while that haven’t been concerned. To improve the detection accuracy of crack measurement, this paper focuses on making clear the tensile stress effect on the crack depth quantification in ferromagnetic materials by ECPT. A theoretical analysis, including the ECPT theory, the stress equivalent field theory and the μ-Hσ curve, has been conducted and verified by experiments. The results show that the direction and magnitude of the stress have strong influences on the thermal features. And the tensile stress can increase the linear slope of crack depth quantitative curve. Further, probability of detection (POD) curves prove that the tensile stress enhances the detection capability of shallow cracks by ECPT.

A Kriging-Based Magnetic Flux Leakage Method for Fast Defect Detection in Massive Pipelines

Abstract Systems in service continue to degrade with the passage of time. Pipelines are among the most common systems that wear away with usage. For public safety, it is of utmost importance to monitor pipelines. Magnetic flux leakage (MFL) testing is a widely used nondestructive evaluation (NDE) technique for defect detections within the pipelines, particularly those composed of ferromagnetic materials. Pipeline inspection gauge (PIG) procedure based on line scans can collect accurate MFL readings for defect detection. However, in real world, applications involving large pipe sectors such as extensive scanning techniques are extremely time consuming and costly. In this article, we develop a fast and cheap methodology that does not need MFL readings at all the points used in traditional PIG procedures but conducts defect detection with similar accuracy. We consider an under-sampling based scheme that collects MFL at uniformly chosen random scan points over large lattices instead of extensive PIG scans over all lattice points. On the basis of readings from the chosen random scan points, we use kriging to reconstruct MFL readings. Thereafter, we use thresholding-based segmentation on the reconstructed data for detecting defective areas. We demonstrate the applicability of our methodology on synthetic data generated using finite element models and on MFL data collected via laboratory experiments. In these experiments, spanning a wide range of defect types, our proposed novel MFL-based NDE methodology is witnessed to have operating characteristics within the acceptable threshold of PIG-based traditional methods and thus provide an extremely cost-effective, fast procedure with competing error rates.

Недеструктивная объемная микроскопия в изучении особенностей биологической адаптации среди ископаемых и современных Homo

We apply non-destructive volumetric technique for evaluation of vascular net density in compact bone. Segmentation of Haversian canals and accurate estimation of their relative volume fraction gives the opportunity to estimate the density and capacity of the vascular system of the bone tissue in a proxy way. Radiological images of dorsal compact of medial and distal phalanges were studied (Neanderthals from Altai and Europe; CroMagnons; recent humans of Arctic and African origin). Results. High vascularization of compact clearly demonstrates that European Neanderthals and the majority of AMH were adapted to the Glacial Age. But Kostenki 14 (Eastern Europe) and Strashnaya 4 (Altai) have features in common with humans of recent tropic origin. Specimens of Neanderthals which lived in Altai region where glaciers never occurred are more diverse. Hypothetically the milder climate favored the existence of a wider adaptive norm reflecting patterns of former environments. Somewhat ambiguous morphological patterns of Denisova 9 and Okladnikov 2, 5 may reflect various episodes of Neanderthal migration to Siberia and their hybridization with people of tropical ancestry, most probably the early AMH. Chagyrskaya Neanderthal demonstrates a hyper-cold adaptation. Conclusion. Diversity in microstructural patterns of the Pleistocene people’s skeletal system gives evidence that both Neanderthals and CroMagnons were polymorphic in their adaptive reactions and presumably included both warm and cold adapted forms.

Condition Assessment of Induced Draught Cooling Towers Located In Different Climatic Regions of India

Induced Draft Cooling Towers (IDCT) are an important industrial structures, which removes the heat absorbed in the circulating cooling water systems of thermal power plants. The cooling tower in general comprises of RCC members’ viz. Column, Beam, Slab, Wall, Louvers, Fanstack Shell etc. The process of operation is itself an important factor which affects the durability of members of IDCTs, due to which the RCC members of IDCT are subjected to varying exposure condition, some members are continuous under water, some are partially submerged, some have alternate drying & wetting and some are completely dry. Due to different exposure conditions of RCC members of these structures generally shows very contrasting states of distress i.e. varying from apparently un-distressed to highly distressed state. Apart from process of operation of IDCTs, the other important factors that affect the durability of these RCC structures are presence of Chloride in water being cooled & Chloride in concrete present during the construction and carbonation due to aging of concrete. The RCC structures were assessed by various Non-Destructive evaluation techniques and deterioration mechanisms were established. The present paper highlights the findings of condition assessment studies of selected IDCTs located in different climatic regions of India.

Estimation of microtexture region orientation distribution functions using eddy current data

Microtexture regions (MTRs) within titanium alloys are collections of grains with similar crystallographic orientation. The presence of MTRs can be detrimental to the life of an engine component; as such, a method to detect and characterize MTRs is needed. One potential technique to characterize MTRs is eddy current (EC) testing, which is a nondestructive evaluation technique that is sensitive to the changes in local conductivity due to changes in local crystallographic orientation. While it has been established in the literature that EC methods are sensitive to the presence of MTRs, work has begun only recently to determine the ability of EC to characterize MTRs. In this work, we develop an algorithm to estimate the orientation distribution function of an MTR of interest using EC data. The method relies on an application of the central limit theorem, and the inverse problem is solved in using a likelihood-free technique. Numerical examples using simulated EC data are shown.

Pulse Compression Favorable Thermal Wave Imaging Techniques for Non-Destructive Testing and Evaluation of Materials

This article highlights the application of pulse compression favorable Frequency Modulated Thermal Wave Imaging (FMTWI) technique for testing and evaluation of Carbon Fibre Reinforced Plastics (CFRP). The concept of InfraRed Image Correlation (IRIC) has been introduced to reconstruct the correlation fringes for the pulse compressed data obtained from the matched filter approach to detect the flat bottom hole defects in a CFRP specimen. Further, comparison has been made with the acquired phasegrams using frequency and time domain based data processing approaches. Obtained results clearly demonstrate the strengths of the proposed IRIC based post-processing scheme in providing the spatio-temporal correlation fringes for thermal Non-Destructive Testing & Evaluation (NDT&E) of CFRP materials.