Nondestructive Evaluation Imaging Research Articles

Nonlinear Beamforming Based on Amplitude Coherence Applied to Ultrasonic Imaging of Coarse-Grained Steels

Abstract This paper deals with ultrasonic imaging in a nondestructive evaluation (NDE) context. In particular, we are focused on the inspection of coarse-grained steels having a heterogeneous composition that creates structural noise in the ultrasonic signals and images. The standard way to beamform the acquired ultrasonic data is by delay-and-sum (DAS). This method is fast but suffers from low signal-to-noise ratio (SNR) for coarse-grained steel inspection. In this paper, we propose to adapt a coherence-based beamformer called pDAS from the medical imaging community. pDAS beamforming is based on DAS structure but includes p-root and p-power before and after summations, respectively. It results in an enhancement of the coherent summation of signals that improves both resolution and contrast. Coherence-based beamformers are known to enhance information whose acoustic response correlates with geometrical information, that is why they decrease grating lobes and side lobes, specular echoes, reconstruction artifacts, and noise due to multiple scattering. In this paper, the pDAS beamformer is proposed for two common acquisition schemes employed in NDE that are plane wave imaging (PWI) and full matrix capture (FMC). The beamformers have been efficiently implemented for parallel computing on graphics processing unit (GPU) in a context of real-time imaging and fast part scanning in NDE. First, experimental results are presented from an austenitic-ferritic sample from the power generation industry that contains side drilled holes (SDH) with diameter 0.4 mm at several depths. pDAS (for p from two to three) shows improvements in terms of SNR and resolution compared to standard DAS, both in PWI and FMC modalities. We also show that the computation cost of pDAS is equivalent to DAS. A real application on a sample containing a fatigue crack connected to the backwall is exposed. We show that pDAS beamformer can enhance crack response compared to grains, but it also decreases unwanted information such as backwall specular echoes and reconstruction artifacts.

Hyperspectral reflectance imaging for nondestructive evaluation of root rot in Korean ginseng (Panax ginseng Meyer).

Root rot of Panax ginseng caused by Cylindrocarpon destructans, a soil-borne fungus is typically diagnosed by frequently checking the ginseng plants or by evaluating soil pathogens in a farm, which is a time- and cost-intensive process. Because this disease causes huge economic losses to ginseng farmers, it is important to develop reliable and non-destructive techniques for early disease detection. In this study, we developed a non-destructive method for the early detection of root rot. For this, we used crop phenotyping and analyzed biochemical information collected using the HSI technique. Soil infected with root rot was divided into sterilized and infected groups and seeded with 1-year-old ginseng plants. HSI data were collected four times during weeks 7-10 after sowing. The spectral data were analyzed and the main wavelengths were extracted using partial least squares discriminant analysis. The average model accuracy was 84% in the visible/near-infrared region (29 main wavelengths) and 95% in the short-wave infrared (19 main wavelengths). These results indicated that root rot caused a decrease in nutrient absorption, leading to a decline in photosynthetic activity and the levels of carotenoids, starch, and sucrose. Wavelengths related to phenolic compounds can also be utilized for the early prediction of root rot. The technique presented in this study can be used for the early and timely detection of root rot in ginseng in a non-destructive manner.

Far-field ultrasonic imaging using hyperlenses

Hyperlenses for ultrasonic imaging in nondestructive evaluation and non-invasive diagnostics have not been widely discussed, likely due to the lack of understanding on their performance, as well as challenges with reception of the elastic wavefield past fine features. This paper discusses the development and application of a cylindrical hyperlens that can magnify subwavelength features and achieve super-resolution in the far-field. A radially symmetric structure composed of alternating metal and water layers is used to demonstrate the hyperlens. Numerical simulations are used to study the performance of cylindrical hyperlenses with regard to their geometrical parameters in imaging defects separated by a subwavelength distance, gaining insight into their construction for the ultrasonic domain. An elegant extension of the concept of cylindrical hyperlens to flat face hyperlens is also discussed, paving the way for a wider practical implementation of the technique. The paper also presents a novel waveguide-based reception technique that uses a conventional ultrasonic transducer as receiver to capture waves exiting from each fin of the hyperlens discretely. A metallic hyperlens is then custom-fabricated, and used to demonstrate for the first time, a super-resolved image with 5X magnification in the ultrasonic domain. The proposed hyperlens and the reception technique are among the first demonstrations in the ultrasonic domain, and well-suited for practical inspections. The results have important implications for higher resolution ultrasonic imaging in industrial and biomedical applications.

Terahertz polarimetry with a monolithic metasurface

The state of polarization (SoP) is a fundamental property of electromagnetic radiation that can carry a rich set of important information in light transmitted through a test sample. Despite a wide range of applications in material identification, (thin-film) characterization, and defect analysis, the SoP remains difficult to exploit—especially at terahertz frequencies since its measurement requires complex apparatuses with multiple moving parts. We have addressed these challenges by designing a metasurface polarimeter (MSP) that incorporates the entire functionality of a division of aperture polarimeter (DoAP) with high efficiency into a single silicon layer without the need for moving parts. Collective simulations are in perfect agreement with experimental data, both confirming the intended operation. Furthermore, we present an automated analysis algorithm that allows for the complete determination of the SoP from a single image with an experimental accuracy of 92.1% ± 4.2%, following an initial calibration. We anticipate that the presented MSP will find applications in polarimetric sensing and imaging for non-destructive evaluation at terahertz frequencies.

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.

Pulsed thermal imaging for non-destructive evaluation of hot gas path coatings in gas turbines

ABSTRACT To address global research in energy technologies, a UK–US collaboration was setup to look at implications in the use of alternative gas turbine liquid/gaseous fuels and first-generation IGCC-derived syngas. The development of predictive models for deposition, corrosion and component living in gas turbines operating on such novel fuel gases is now being developed. Linked to this, the non-destructive inspection of hot gas path components needs to be refined and the life prediction models utilising thermal barrier coatings need to be validated to enable the on-going assessment of the remnant lives of components during their use. Thermal barrier coatings (TBCs) have been critical to the operation of gas turbines in aircraft and land-based applications. As the engine demands increase with respect to operational temperature and efficiency, so has the requirement for TBCs, both from the perspective of their performance (thermal conductivity, durability) as well as their reliability. Because TBCs play critical role in protecting the underlying super alloy, their failure (spallation) cause accelerated component damage leading to unplanned outage. Therefore, it is important to inspect and monitor the TBC condition to assure its quality and reliability. Non-destructive evaluation (NDE) methods would allow for direct determination of TBC thermal conductivity on coated components and, therefore, they can be used to inspect the quality of as processed components and monitor TBC degradation during service. This paper presents a new method, the pulsed thermal imaging–multilayer analysis (PTI–MLA) method, which can measure the coating thermal conductivity and heat capacity distributions for coatings on different substrates and thickness. NDE methods were also evaluated based on preliminary experimental results for TBC samples that were thermal cycled to various lifetimes to monitor TBC degradation and predict TBC life. Initial insight into the TBC response with painted and unpainted surfaces is also discussed to demonstrate next steps.

Super-Resolution Ultrasound Lamb Wave NDE Imaging of Anisotropic Airplane Laminates via Deconvolutional Neural Network

A deconvolutional neural network (DNN) is integrated into the ultrasound (UT) pulse-echo Lamb wave nondestructive evaluation (NDE) imaging technique to achieve subwavelength super-resolution defect images for the application of anisotropic composite airplane-laminated structures. First, numerical simulation has been performed to simulate the multilayer velocity–frequency dispersion relation of the symmetric and antisymmetric Lamb wave modes. Then, a super-resolution DNN is developed with all Lamb wave modes as the convolutional kernels to obtain the subwavelength defects image of the laminated structures. After that, the effectiveness of the pulse-echo Lamb wave NDE imaging technique is verified by the experimental test of a standard aluminum metal plate with three calibration holes of 2/3/5 mm diameters at the UT center frequency of 2 MHz and a line defect. Finally, the experiment of the pulse-echo Lamb wave NDE imaging technique is carried out with an L-joint coupon sample made of anisotropic graphite–epoxy airplane materials. The comparison between the experimental result and the conventional pitch-catch C-scan shows that the Lamb wave NDE technique can reveal more details of the defects, indicating its promising application in anisotropic layers’ structures defects inspection.

Model-Based Study of a Metamaterial Lens for Nondestructive Evaluation of Composites

Abstract Composites are being increasingly used in various industries due to their lower cost and superior mechanical properties over traditional materials. They are nevertheless vulnerable to various defects during manufacturing or usage which can cause failure of critical engineering structures. Hence, there is a growing need for nondestructive evaluation (NDE) of composites to detect such defective structures and avoid significant loss and damages. Microwave NDE has several advantages over other existing NDE techniques for detecting defects or faults in non-conducting composites or dielectrics. One of the primary benefits of microwaves is large probe-standoff distances which allow for rapid scan times. However, the resolution of such far-field microwave sensors is diffraction limited. Metamaterial-based lens, also known as “superlens,” can achieve resolution beyond the diffraction limits due to its unique electromagnetic (EM) properties. This contribution focuses on the physical design of a metamaterial lens. The theory underlying the design of a metamaterial lens is presented followed by simulation and experimental results. This paper also investigates the feasibility of using the metamaterial lens for improving the resolution of microwave imaging in NDE of composites.

Enhanced Ultrasonic Imaging and Non-Destructive Evaluation Using Angle-of-Arrival Estimation in Dimension-Reduced Beam Space

Abstract Robust defect detection in the presence of grain noise originating from material microstructures is a challenging yet essential problem in ultrasonic non-destructive evaluation (NDE). In this paper, a novel method is proposed to suppress the gain noise and enhance the defect detection and imaging. The defect echo and grain noise are distinguished through analyzing the spatial location where the echo is originating from. This is achieved by estimation of the angle of arrival (AOA) of the returned echo and evaluation of the likelihood that the echo is reflected from the point where the array is focused or otherwise from the random reflectors like the grain boundaries. The method explicitly addresses the statistical models of the defect echoes and the spatial noise across the array aperture, as well as the correlation between the flaw signal and the interfering echoes; estimates the AOA and the likelihood in a dimension-reduced beam space via a linear transformation; and determines a weighting factor based on the mean likelihood. The factors are then normalized and utilized to correct and weigh the NDE images. Experiments on industrial samples of austenitic stainless steel and INCONEL Alloy 617 are conducted with a 5 MHz transducer array, and the results demonstrate that the grain noise is reduced by about 20 dB while the defect reflection is well retained, thus the great benefits of the method on enhanced defect detection and imaging in ultrasonic NDE are validated.

Enhancement of microwave time reversal imaging using metallic reflectors

There is a growing interest in the use of composites in several industries such as aerospace, automotive and civil infrastructure due to their unique properties such as light-weight, corrosion resistance and excellent thermo-mechanical properties. However, it is critical to ensure that no defects, such as disbonds, voids and delaminations are introduced during fabrication or during service. A variety of nondestructive evaluation (NDE) techniques have been proposed and developed to detect such defects that can compromise the integrity of these structures. Microwave NDE techniques are well suited for inspection of dielectric materials such as composites because of the ability of electromagnetic waves to interact with these materials. Far field electromagnetic inspection systems have the capability of rapid, large area inspection at large stand-off distance. However the diffraction limits restrict the resolution of conventional far field imaging. This contribution focuses on enhancing the resolution of microwave far field imaging using metal reflectors to increase the virtual aperture of the receiver array. Model based studies demonstrate the feasibility and robustness of this approach and also determine the limits of this technique. Preliminary experimental results based on a time reversal cavity environment validates the approach for enhancing the resolution of microwave NDE imaging.

Comparison of NMR and microwave NDE methods for defect detection in composite structures

Abstract New advanced non-destructive evaluation (NDE) methods such as nuclear magnetic resonance (NMR) imaging and microwave NDE methods are being developed for their advantages and high resolution for defect detection in composite structures. Glass/epoxy composite structures are being used for many applications in industry. Often, glass/epoxy composite structures are used along with rubber lining in oil and gas pipe industry. Rubber is adhesively bonded to composite inner surface to meet the requirements. The interface of glass/epoxy composite and rubber lining is critical. Any de-bond (separation of adhesively bonded liner from composite surface) at the interface may lead to failure of composite structure due to corrosive gases and liquids. The present paper reports application of proton single sided NMR method to evaluate the de-bonds of rubber liner with composite. Results are compared with microwave NDE technique which is an advanced non-contact inspection method. Results indicate application of both these techniques for evaluation of bonded interfaces. Advantages of both the techniques over conventional techniques have been discussed. De-bonds within rubber lining were also detected and correlated.

Artificial neural networks based quantitative evaluation of subsurface anomalies in quadratic frequency modulated thermal wave imaging

Quantitative subsurface analysis with increased reliability is fascinating the post processing research in infrared imaging for non destructive evaluation. Accompanied by a variety of post processing approaches, non stationary thermal wave imaging has been emerging as a reliable technique to cater to anomaly detection for a wide range of materials despite its lack of quantitative evaluation. This paper proposes a classification and regression based quantitative post processing modality to characterize subsurface anomalies using quadratic frequency modulated thermal wave imaging and validate it with the experimentation carried over a carbon fiber reinforced and glass fiber reinforced plastic specimens along with a suitable mathematical model based on thermal wave propagation principles. Subsurface details have been visualized in terms of their depths where their detection capability and reliability have been assessed using signal to noise and probability of detection respectively.

Nondestructive Imaging of Packaged Microelectronics using Pulsed Terahertz Technology

Abstract This work presents the use of terahertz reflection imaging for nondestructive evaluation of packaged microelectronics. Power MOSFETs and SRAM devices are placed in a pulsed terahertz imaging system in the reflection mode with an incident angle of 30°. From the received signal at each point on the sample under test, the internal structure of the device can be clearly seen. For transistors, terahertz nondestructive imaging has been successful in determining die size and location as well as the bond wire size, number, and connections. High-pass frequency filters are utilized to enhance the image quality for viewing the bond wires. In addition, the terahertz B-scans are used to determine additional information including the vertical position of the bond wires and the die inside the packaged device. For the SRAM, the terahertz nondestructive imaging shows similar effectiveness in defining the layout of the metal connections inside the package and the wire positions. Thus terahertz imaging is shown to have a strong potential for nondestructive evaluation of these devices.

A Statistical Framework for Improved Automatic Flaw Detection in Nondestructive Evaluation Images

ABSTRACTNondestructive evaluation (NDE) techniques are widely used to detect flaws in critical components of systems like aircraft engines, nuclear power plants, and oil pipelines to prevent catastrophic events. Many modern NDE systems generate image data. In some applications, an experienced inspector performs the tedious task of visually examining every image to provide accurate conclusions about the existence of flaws. This approach is labor-intensive and can cause misses due to operator ennui. Automated evaluation methods seek to eliminate human-factors variability and improve throughput. Simple methods based on peak amplitude in an image are sometimes employed and a trained-operator-controlled refinement that uses a dynamic threshold based on signal-to-noise ratio (SNR) has also been implemented. We develop an automated and optimized detection procedure that mimics these operations. The primary goal of our methodology is to reduce the number of images requiring expert visual evaluation by filtering out images that are overwhelmingly definitive on the existence or absence of a flaw. We use an appropriate model for the observed values of the SNR-detection criterion to estimate the probability of detection. Our methodology outperforms current methods in terms of its ability to detect flaws. Supplementary materials for this article are available online.

Target Localization Using Microwave Time-Reversal Mirror in Reflection Mode

Time-reversal (TR) focusing is based on the fact that when a wave solution is reversed in time and back propagated, it focuses back at the source. TR techniques using microwave measurements have proved to be promising for radar detection and defect imaging in nondestructive evaluation of dielectric samples. This paper presents a TR technique for target detection and localization applications using far-field microwave measurements in reflection mode. Simulation results investigate the feasibility and robustness of this approach and determine the limits of this technique. Experimental results based on reflection mode measurements validate the approach for the detection of source and closely spaced multiple dielectric targets.

A single-phase elastic hyperbolic metamaterial with anisotropic mass density.

Wave propagation can be manipulated at a deep subwavelength scale through the locally resonant metamaterial that possesses unusual effective material properties. Hyperlens due to metamaterial's anomalous anisotropy can lead to superior-resolution imaging. In this paper, a single-phase elastic metamaterial with strongly anisotropic effective mass density has been designed. The proposed metamaterial utilizes the independently adjustable locally resonant motions of the subwavelength-scale microstructures along the two principal directions. High anisotropy in the effective mass densities obtained by the numerical-based effective medium theory can be found and even have opposite signs. For practical applications, shunted piezoelectric elements are introduced into the microstructure to tailor the effective mass density in a broad frequency range. Finally, to validate the design, an elastic hyperlens made of the single-phase hyperbolic metamaterial is proposed with subwavelength longitudinal wave imaging illustrated numerically. The proposed single-phase hyperbolic metamaterial has many promising applications for high resolution damage imaging in nondestructive evaluation and structural health monitoring.

ACTIVE SPECTRAL IMAGING NONDESTRUCTIVE EVALUATION (SINDE) CAMERA

A proof-of-concept video camera for active spectral imaging nondestructive evaluation has been demonstrated. An active multispectral imaging technique has been implemented in the visible and near infrared by using light emitting diodes with wavelengths spanning from 400 to 970 nm. This shows how the camera can be used in nondestructive evaluation to inspect surfaces and spectrally identify materials and corrosion.

Enhanced image processing and archiving capabilities of magneto-optical imaging for non-destructive evaluation

In its current state, the wide acceptance of the Magneto-Optical Imaging (MOI) technique is hindered due to noise, lack of recordable results, and impossibility of data post-processing. This paper presents some add-ons made to a commercial MOI system to ease the image interpretation, archiving and reporting of the results. In addition, a few image processing techniques are also employed in an attempt to perform automatic flaw detection. The recording capability of the MOI instrument output images was addressed by digitizing the video signal in video or image files. To help with the identification of the damage location and distance between images, a rotary quadrature encoder was mounted onto the MOI scan head. The use of the encoder allowed the identification of the inspection location with respect to a reference position, such as the beginning of the scan. Moreover, it allowed saving images at fixed intervals, which were then stitched into a single image, thus simplifying the post inspection analysis process. Both live and post-inspection image processing capabilities were made available. Implemented image processing included background subtraction, de-noising, contrast adjustment and morphological operation, among others. Contrast stretching transform and background subtractions were found to be among the most powerful techniques that could be used in simplifying the image interpretation.

Laser Lock-in Thermal Wave Imaging for Nondestructive Evaluation

This paper presents a new laser lock-in thermography (LLT) technique for nondestructive evaluation. LLT utilizes a modulated continuous wave laser beam as a heat source to obtain high fidelity thermal wave images even at the presence of background heat disturbances. The thermal waves propagating along the surface and through-the-thickness directions of a structure are visualized using newly developed laser lock-in amplitude and phase images, enhancing the detectability of surface and subsurface defects. The LLT technique is numerically investigated and experimentally validated using thermal images obtained from a steel specimen with low emissivity.

Nonuniform Manual Scanning for Rapid Microwave Nondestructive Evaluation Imaging

Wideband synthetic aperture radar (SAR) technique is a robust imaging tool for microwave and millimeter-wave imaging such as nondestructive evaluation applications. In this paper, we present an alternative method to conventional raster scanning involving manually selected and nonuniformly distributed measurement positions, enabling the production of complete SAR images-potentially using only a fraction of the conventionally required measured data. The user is kept informed throughout the scanning process by a stream of real-time SAR images. Finally, data reconstruction algorithms are used offline to produce high-quality images with considerably lower background noise and image artifacts as compared to the real-time images. We also introduce a novel reconstruction method that uses the components of the SAR algorithm to advantageously exploit the inherent spatial information contained in the data, resulting in a superior data reconstruction and final SAR image. This paper presents the measurement methodology along with the images obtained from three different specimens of increasing geometrical complexity.