Nondestructive Testing Imaging Research Articles

Detection and classification of invisible weld defects by magneto-optical imaging under alternating magnetic field excitation

Aiming at the difficult to detect invisible weld defects, a magneto-optical (MO) imaging non-destructive testing (NDT) system excited by an alternating magnetic field is proposed for feature extraction and detection classification of invisible weld defects. The relationship between the MO image features and the magnetic field intensity is analyzed based on the Faraday MO effect. A magnetic dipole model is proposed to study the magnetic field distribution on weld defect. A three-dimensional finite element model of invisible weld defects (with a width of 0.01 mm) is established, and the distribution of leakage magnetic field for different types of invisible defects is analyzed. In order to detect different invisible weld defects under the excitation of alternating magnetic field, MO imaging NDT experiments are carried out. The effectiveness of the finite element model is verified by the experiment. The gray value of the MO image can match the corresponding leakage magnetic field intensity. The Tamura method and gray-level co-occurrence matrix (GLCM) method are used to extract the texture features of natural invisible weld defect’s MO image, and these texture features of MO images are used as input data for the defect classification model established using back propagation (BP) neural network. Experimental results show that the classification accuracy of the GLCM + Tamura-BP model is higher than that of the GLCM-BP model, and its overall classification accuracy reaches 91.1%, indicating that this model can effectively and accurately classify natural invisible weld defects.

Tunable Energy Spectrum Betatron X-ray Sources in Plasma Wakefield

Abstract The X-ray source with tunable energy spectrum has a wide range of application requirements in different scenarios because of its different penetration. However, existing X-ray sources face difficulties in energy regulation. In this paper, we prsent a scheme for tuning the energy spectrum of Betatron X-ray generated from a relativistic electron bunch oscillating in plasma wakefield. The center energy of the X-ray source can be tuned from several keV to several hundred keV by changing the plasma density, extending the control range by an order of magnitude. At different central energies, the brightness of Betatron radiation is in the range of 3.7 × 1022 to 5.5 × 1022 photons/(0.1%BW·s·mm2·mrad2), and the photon divergence angle is about 2 mrad. This high-brightness, energy-controlled betatron source could open a way to a wide range of applications requiring photons of specific energy, such as phase-contrast imaging in medicine, non-destructive testing and material analysis in industry, and imaging in nuclear physics.

Fabrication of elliptical-silica microfiber for ultrasound detection.

Elliptical shape microfiber enables many higher order modes compared with a circular microfiber. The small difference in the optical path length among many modes enabled multi-resonance peaks with high contrast in Mach-Zehnder (MZI) interferometers, which allows a large dynamic range and minimum detection sensitivity for broadband ultrasound sensing. In this paper, we present the design and fabrication of an ultra-compact elliptical-silica microfiber utilizing off-axis flame-drawing for ultrasound detection. The narrow transmission peak showed high contrast for ultrasensitive ultrasound wave detection. With a major-axis diameter of 6.25 µm, the elliptical-silica microfiber sensor exhibits a broadband ultrasound frequency response spanning from 20 kHz to 38.5 MHz. Furthermore, it achieves a signal-to-noise ratio (SNR) of up to 80 dB at 1 MHz, which is the resonance frequency of the microfiber and the linear response under driving voltages of 3-10 V for the PZT ultrasound generator. This low-cost microfiber sensor offers exceptional sensitivity across a broad ultrasonic bandwidth response, making it an ideal choice for nondestructive testing (NDT) and medical imaging applications. Its compact size and immunity to electric and magnetic fields further enhance its utility in various environments.

Inorganic metal oxide material BaSiO3:Eu2+ for convenient 3D X-ray imaging

X-ray storage phosphors are found wide-ranging applications in medical diagnosis, nondestructive testing and X-ray imaging. However, designing X-ray storage phosphors with high electron storage capacity still poses a daunting challenge. In this study, we designed a fluorescent powder based on Eu2+-doped BaSiO3, demonstrating excellent optical information storage characteristic. Under high-energy X-ray filling, shallow traps exhibit low electron capacity and only produce weak afterglow, which greatly helps to minimize the impact of afterglow on the image quality during X-ray imaging. In addition, the deep traps at 1.01 eV filled with high-energy X-ray allow the material to store information for a long time. The crystal structure, photoluminescence (PL) and thermoluminescence (TL) spectra were studied systematically. The electron trapping properties of the material were analyzed using TL spectroscopy. Finally, we fabricated a flexible film with phosphors, the flexible film has been utilized to demonstrate high-quality real-time X-ray imaging and achieve time-delayed X-ray imaging of curved objects, such as flexible circuit boards.

Highly efficient broadband near-infrared luminescence phosphors Ca3MgSn0.5Zr0.5Ge3O12:Pr3+,Cr3+ for multifunctional applications in pc-LEDs field

Exploring high-performance broadband near-infrared (NIR) emitting materials is crucial for the development of NIR devices. In this study, Ca3MgSn0.5Zr0.5Ge3O12:Cr3+ and rare earth ion Pr3+ co-doped Ca3MgSn0.5Zr0.5Ge3O12:Pr3+,Cr3+ phosphors were successfully synthesized. By utilizing time-resolved emission spectroscopy (TRES), photoluminescence (PL) spectra, and fluorescence decay curve, the Ca3MgSn0.5Zr0.5Ge3O12:Cr3+ phosphor is determined to exhibit a broadband emission (650–1150 nm) with a peak at 795 nm due to Cr3+ occupying multiple cationic sites. Ca3MgSn0.5Zr0.5Ge3O12:0.1Cr3+ has excellent thermal stability (86%@425 K), and co-doping Pr3+ ions into Ca3MgSn0.5Zr0.5Ge3O12:0.1Cr3+ obtains highly efficient NIR emission. The Ca3MgSn0.5Zr0.5Ge3O12:0.01Pr3+,0.1Cr3+ phosphor has quantum yield of 89.4% thanks to the energy transfer effect from Pr3+ to Cr3+. The fabricated NIR phosphor-converted light emitting diodes (pc-LEDs) by integrating the blue chip with Ca3MgSn0.5Zr0.5Ge3O12:0.01Pr3+,0.1Cr3+ has diverse applications including night vision, non-destructive testing, and medical imaging.

Progress and comparison in nondestructive detection, imaging and recognition technology for defects of wafers, chips and solder joints

ABSTRACT As an essential part of integrated circuit, chip manufacturing has increasingly demanding requirements for quality, cost and others. Some technical limitations and the development direction of miniaturisation and high density have led to defects in the manufacturing process, which affect the performance and life of the chip. Therefore, the detection, identification and classification of defects are very important to improve the chip reliability. Based on the orderly and concise literature research, this paper focuses on a comprehensive review of the main research results in the field of non-contact non-destructive testing imaging methods for chip defects. Firstly, various defects that may occur in the chip design and packaging process are introduced. Then the contact detection methods including manual and probe method are clarified, and the principles, properties and development applications of NDT methods are introduced in detail, also the defect identification methods after imaging are briefly introduced. Moreover, the advantages and limitations of NDT technologies are summarised through comparative studies. Finally, the future development trend of non-destructive testing methods is predicted. This work hopes to provide some reference for the non-destructive testing of chips, which is of great significance for the health testing of chips in the electronics manufacturing industry.

Automatic estimation of surface and probe location for 3D imaging with bidimensional arrays

Ultrasound imaging for Non Destructive Testing is frequently performed in an immersion setup, where water is used as coupling medium between the probe and the component under test. For the computation of the time delays needed for beam-forming, the shape of the component surface and probe location and orientation (PLO) must be known. In this work we develop methods for the automatic detection of the surface and the estimation of PLO for 2D array probes. In particular, the methods developed apply to three types of elementary surfaces which are usually found in industrial and structural components: planes, cylinders and spheres. The methods use the measured surface echoes Time of Flight (TOF) to fit parametric models based on ray propagation and reflection on the surface, giving the coordinates and Euler angles that define the PLO relative to the component under test. Validation experiments with four test specimens representing the three types of surfaces are presented . The accuracy and precision of estimated PLO coordinates and angles are analyzed, and a Total Focusing Method (TFM) imaging example is shown achieving a correct detection of artificial defects in the component for a different PLOs.

Synergistic effect of dual-site occupation and activators confinement realizing an efficient ultra-broadband NIR emitter

Broadband near-infrared (NIR) phosphor-conversion light-emitting diode (pc-LED) devices have an extensive application prospect in night vision monitoring, nondestructive testing, and biomedical imaging. In this work, the ultra-broadband NIR emission produced by the chromium-activated NaZn(PO3)3 phosphor with two-site occupation peaks at around 900 nm with a full width at half-maximum (FWHM) of 218 nm. Time-resolved spectroscopic techniques and steady-state fluorescence spectra coupled with crystal structure confirm the multiple occupations of the chromium ion. Notably, the NaZn(PO3)3: Cr3+ phosphors exhibit an internal quantum efficiency (IQY) of 80.6 % and an external quantum efficiency (EQY) of 35.4 %, which may originate from the activators confinement, direct band-gap property, and high absorbance. To better comprehend the connection between structure and luminescence capabilities, the band structure, crystal field strength parameters, fluorescence lifetime, and thermal stability were all thoroughly investigated. Finally, the optimal sample has demonstrated its application in the quantitative analysis of ethanol/water mixtures. The results provide a novel perspective for the rational design of desired emitters.

Analysis of Imaging Characteristics of Wide-field Lobster Eye Lens

The lobster-eye lens is a reflected type focusing optics. It can be used for backscattering imaging that is a single-sided access technology for homeland security, detection of improvised explosive devices, non-destructive testing, and medical imaging. The aim of this study was to investigate the imaging characteristic of meridional lobster-eye lens with a planar imaging surface. The larger the field of view, the greater the spherical aberration, and the larger the field curvature of the edge field of view. Both spherical aberration and field curvature increase the size of the focal spot, and the images become blurry. Rays with a large angle of grazing incidence have large spherical aberration and curvature. The reflectivity of these rays drops sharply as the energy of photons increases. Therefore, spherical aberration and field curvature have a greater effect on photons with low energy. These conclusions can help improve the design of a lobster-eye lens for wide-field imaging applications.

Isogeometric multi-resolution full waveform inversion based on the finite cell method

Full waveform inversion (FWI) is an iterative identification process that serves to minimize the misfit of model-based simulated and experimentally measured wave field data. Its goal is to identify a field of parameters for a given physical object. For many years, FWI is very successful in seismic imaging to deduce velocity models of the earth or of local geophysical exploration areas. FWI has also been successfully applied in various other fields, including non-destructive testing (NDT) and biomedical imaging. The inverse optimization process of FWI relies on forward and backward solutions of the (elastic or acoustic) wave equation, as well as on efficient computations of adequate optimization directions. Many approaches employ (low order) finite element or finite difference methods, using parameterized material fields whose resolution is chosen in relation to the elements or nodes of the discretized wave field. In our previous paper (Bürchner et al., 2023), we investigated the potential of using the finite cell method (FCM) as the wave field solver. The FCM offers the advantage that highly complex geometric models can be incorporated easily. Furthermore, we demonstrated that the identification of the model’s density outperforms that of the velocity — particularly in cases where unknown voids characterized by homogeneous Neumann boundary conditions need to be detected. The paper at hand extends this previous study in the following aspects: The isogeometric finite cell analysis (IGA-FCM) – a combination of isogeometric analysis (IGA) and FCM – is applied as the wave field solver, with the advantage that the polynomial degree and subsequently also the sampling frequency of the wave field can be increased quite easily. Since the inversion efficiency strongly depends on the accuracy of the forward and backward wave field solutions and of the gradients of the functional, consistent, and lumped mass matrix discretization are compared. The resolution of the grid describing the unknown material density – thus allowing to identify voids in a physical object – is then decoupled from the knot span grid. Finally, we propose an adaptive multi-resolution algorithm that locally refines the material grid using an image processing-based refinement indicator. The developed inversion framework allows fast and memory-efficient wave simulations and object identification. While we study the general behavior of the proposed approach using 2D benchmark problems, a final 3D problem shows that it can also be used to identify void regions in geometrically complex spatial structures.

Full Waveform Inversion for NDT using ultrasonic linear arrays

Ultrasonic (UT) imaging is a widespread technique for nondestructive testing (NDT). The state-of-the-art UT image reconstruction algorithms are based on delay-and-sum (DAS) operations, which assume constant acoustic velocity across the tested objects and also neglects nonlinear effects such as diffractions and multiple reflections. These assumptions limit the reconstruction capabilities of DAS-based algorithms, especially for complex objects composed by several materials. In seismology, Full Waveform Inversion (FWI) methods have been used to obtain subsurface properties based on scattered and transmitted sound waves - which is a very similar problem to ultrasonic imaging in NDT - using the full wave information, showing promising results. In this paper, we present the application of FWI in NDT using simulated data representing acquisitions with a common linear array transducer. We review the theoretical formulation of FWI and discuss some difficulties that arise when it is applied to NDT. Image reconstruction is performed using both a state-of-the-art DAS algorithm, namely the Total Focusing Method, and FWI. The implementation targets a GPU platform, using the CUDA API. This leverages the highly parallelizable nature of the simulations and the FWI algorithm. The obtained results show that FWI can show more internal structures than TFM, with less information about the specimen. To foster further development, all source codes are provided.

Damage Characteristics of Asphalt Stabilized Macadam Under Freeze-thaw Action

In order to study the freeze-thaw resistance of asphalt stabilized macadam asphalt pavement in cold regions, the asphalt stabilized macadam specimens were subjected to freeze-thaw cycles at different times. Based on CT non-destructive testing and digital image processing technology, the change laws of porosity, void number and void equivalent diameter of asphalt stabilized macadam specimens were studied, so as to analyze the freeze-thaw damage characteristics of asphalt stabilized macadam from the micro level, The effect of adding 2% SBS modifier on the freeze-thaw resistance of asphalt stabilized macadam was studied. The results show that with the increase of freeze-thaw times, the porosity and the number of voids of asphalt stabilized macadam increases gradually, while the equivalent diameter of voids decrease first and then increase; The addition of 2% SBS can hinder the development of void connectivity and the generation of new voids, and improve the water damage resistance of asphalt stabilized macadam.

Metasurface Optics With On-Axis Polarization Control for Terahertz Sensing Applications

Non-destructive testing and imaging of materials with unknown properties are important applications of terahertz technology. Different contrast forming methods are available to obtain diverse information on the imaged region, including intensity, color, phase and polarization. Polarimetric imaging is relatively under-investigated owing to the difficulty in its implementation with complex optical arrangements. In this paper we present the design and monolithic fabrication of an anisotropic metasurface that incorporates several beam forming functions in a single layer with high efficiency thus simplifying instrument construction. The probe beam generated by the metasurface consists of an orthogonally polarized pair of collinear Bessel beams that create a well-defined on-axis change of polarization. The metasurface is integrated into a polarimetric imaging microscope for 3D beam profiling and sensing experiments at 2.52 THz. An analytical model to describe the on-axis polarization variation was found to be in excellent agreement with both finite-difference time-domain (FDTD) simulations and the experimental results. The setup was used to measure the refractive index and diattenuation of homogeneous sample regions in a proof-of-principle application. We anticipate this technology will find future application in non-destructive testing and polarimetric imaging of polymer composites and 3D profilometry of reflective surfaces.

Effect of pore structure on compressive strength and permeability of planting recycled concrete

The relationship between strength, permeability, and pore structure of planting recycled concrete (PRC) was investigated using industrial computed tomography non-destructive testing technology and image analysis methods. An increase in the aggregate particle size and porosity increased the pore size and fractal dimension, and the relationship between the compressive strength and porosity conformed to the Ryshkewitch model. The fractal dimension had a weaker influence on compressive strength and permeability than did aperture size and porosity. Although vegetation growth reduced the compressive strength and permeability coefficient of PRC, the rainwater infiltration and vegetation compatibility of PRC was confirmed.

Magneto-optical imaging nondestructive testing of welding defects based on image fusion

Improving the visual effect of welding defect detection is a key research area of magneto-optical imaging nondestructive testing technology. Finite element analysis and magneto-optical image simulation are used to analyze the characteristics of magneto-optical imaging detection under rotating excitation. Through the stripe analysis of simulated magneto-optical images, it is found that the multi-frame magneto-optical images at defects have low discrete degree of gray value. Therefore, an image fusion method based on pixel standard deviation is proposed for the welding defect detection of magneto-optical imaging. Fast guide filtering is applied to the magneto-optical images of welding defects under rotating excitation. Pixel standard deviation is used to fuse multi-frame magneto-optical images, and image enhancement and rendering are used to improve the visual effect of welding defect detection. The experimental results show that the fast guided filter can improve the speed of image preprocessing and ensure good image smoothing effect. Compared with other image fusion algorithms, the proposed method can significantly improve the image quality of magneto-optical imaging detection, and does not require screening of magneto-optical images. This method has the advantages of tolerating frame drops in acquisition and excellent generalization performance, enabling fast and efficient nondestructive testing of welding defects.

Improving Magnetic Field Response of Eddy Current Magneto-Optical Imaging for Defect Detection in Carbon Fiber Reinforced Polymers

A large number of carbon fiber reinforced polymers have been applied to aircraft and automobiles, and many nondestructive testing methods have been studied to detect their defects. Eddy current magneto-optical imaging nondestructive testing technology has been widely used in the detection of metal materials such as aircraft skin, but it usually requires a large excitation current and, at present, can only detect metal materials with high conductivity. In order to take full advantage of the innate benefits and efficiency of eddy current magneto-optic imaging and enable it to detect defects in carbon fiber reinforced polymers with weak conductivity, it is necessary to improve the magnetic field response of the eddy current magneto-optic imaging system and explore suitable excitation and detection methods. The scanning eddy current magneto-optical imaging nondestructive testing device built in this study has improved the magnetic field response of the system, and the eddy current magneto-optical phase imaging testing method has been proposed to detect the crack defects of carbon fiber reinforced polymers. The effectiveness of the method has been verified by simulation and experiment.

Ultrasound pulse generation through continuous-wave laser excited thermo-cavitation for all-optical ultrasound imaging

The optical generation of pulsed ultrasound is attractive to nondestructive testing and biological imaging, especially for those involving narrow operation space or strong electro-magnetic interference. However, conventional techniques based on the photoacoustic effect inevitably required an expensive high-energy short pulsed laser and dedicated preparation of the optically absorptive composite film. Here, a fiber-optic ultrasound pulse transmitter based on continuous-wave (CW) laser triggered thermo-cavitation was demonstrated. The fiber-delivered CW laser light heated the highly-absorptive copper nitrate solution and generated explosive bubbles , which emitted strong ultrasound waves. Omnidirectional ultrasound pulses with an amplitude up to 0.3 MPa and a repetition rate of 5 kHz in the frequency range of 5–12 MHz were obtained by using a 50 mW optical heating power at a wavelength of 980 nm. The fiber-tip ultrasound transmitter was integrated with a polymer-cavity-based fiber ultrasound detector to construct an all-fiber ultrasound endoscopic imaging probe. Without the need for a wavelength-tunable laser, the ultrasound detector was interrogated by CW laser light with a fixed wavelength, coupled with feedback-controlled heating of the cavity to stabilize its spectral fringe. The CW laser-driven fiber ultrasound transmitter, in combination with the photothermally stabilized fiber ultrasound detector, opens new routes for a number of ultrasound-related industrial and biomedical applications.

On acoustic guided wave propagation in reinforced concretes and characterization of interface bonding damages

As a possible method for structural health monitoring, guided waves are excellent for hidden damage diagnosis due to their long propagation distance and high damage sensitivity. The multimodal and dispersion phenomena are the primary challenges in the use of guided wave technology for engineering applications. Currently, plate, thin-walled tube, and rod structures—where multimodality and dispersion are comparatively mild and simple to control—remain the major applications of guided wave technology. For more complicated civil engineering structures, severe multimodal and dispersion phenomena cause more difficult issues. The present work began with the study of round-faced reinforced concrete. The waveguide propagation characteristics are computationally analyzed with the assistance of theoretical calculation methods and sweeping frequency simulation experiments. These analytical tools are then creatively applied to threaded reinforced concrete, and the dispersion characteristics of this complex, axially periodically varying waveguide are successfully analyzed. The phenomenon of frequency band pass/stop is also discussed. In addition, this research provides ideas for nondestructive testing and inverse imaging in this field by means of deep learning of the interface debonding defect characteristics of reinforced concrete with the help of convolutional neural networks. This work can be applied not only to various complex reinforced concrete structures but can also be extended to waveguide propagation analysis and defect size data inversion in various complex periodic structures.

Correction of motion artifact in CL based on MAFusNet.

Computed laminography (CL) is one of the best methods for nondestructive testing of plate-like objects. If the object and the detector move continually while the scanning is being done, the data acquisition efficiency of CL will be significantly increased. However, the projection images will contain motion artifact as a result. A multi-angle fusion network (MAFusNet) is presented in order to correct the motion artifact of CL projection images considering the properties of CL projection images. The multi-angle fusion module significantly increases the ability of MAFusNet to deblur by using data from nearby projection images, and the feature fusion module lessens information loss brought on by data flow between the encoders. In contrast to conventional deblurring networks, the MAFusNet network employs synthetic datasets for training and performed well on realistic data, proving the network's outstanding generalization. The multi-angle fusion-based network has a significant improvement in the correction effect of CL motion artifact through ablation study and comparison with existing classical deblurring networks, and the synthetic training dataset can also significantly lower the training cost, which can effectively improve the quality and efficiency of CL imaging in industrial nondestructive testing.

Massive Ultrasonic Data Compression Using Wavelet Packet Transformation Optimized by Convolutional Autoencoders.

Ultrasonic signal acquisition platforms generate considerable amounts of data to be stored and processed, especially when multichannel scanning or beamforming is employed. Reducing the mass storage and allowing high-speed data transmissions necessitate the compression of ultrasonic data into a representation with fewer bits. High compression accuracy is crucial in many applications, such as ultrasonic medical imaging and nondestructive testing (NDT). In this study, we present learning models for massive ultrasonic data compression on the order of megabytes. A common and highly efficient compression method for ultrasonic data is signal decomposition and subband elimination using wavelet packet transformation (WPT). We designed an algorithm for finding the wavelet kernel that provides maximum energy compaction and the optimal subband decomposition tree structure for a given ultrasonic signal. Furthermore, the WPT convolutional autoencoder (WPTCAE) compression algorithm is proposed based on the WPT compression tree structure and the use of machine learning for estimating the optimal kernel. To further improve the compression accuracy, an autoencoder (AE) is incorporated into the WPTCAE model to build a hybrid model. The performance of the WPTCAE compression model is examined and benchmarked against other compression algorithms using ultrasonic radio frequency (RF) datasets acquired in NDT and medical imaging applications. The experimental results clearly show that the WPTCAE compression model provides improved compression ratios while maintaining high signal fidelity. The proposed learning models can achieve a compression accuracy of 98% by using only 6% of the original data.