Defect imaging with guided waves in a pipe

The inelastic contribution to high resolution images of defects

High-speed non-contact defect imaging for a plate-like structure

This paper discusses a defect imaging technique using signals containing multiple reflected waves, for a plate with complex geometries, in which direct waves from a generating point to a receiving point cannot be measured. This technique utilizes a characteristic of flexural vibrations wherein the amplitude of the received signals is approximately inversely proportional to the thickness of the source of the elastic wave when a laser pulse is applied to the surface of the plate. First, a theoretical modal analysis elucidated that the amplitude distributions obtained by scanning the laser source of the elastic waves consist of thickness distributions and spurious distributions caused by multiple reflections in the plate. The amplitude distributions were then experimentally obtained for a complex-shaped plate with an artificial defect. The distributions were found to consist of a defect image as well as spurious images, and this agreed well with the theoretical discussions. Clearer defect images with small spurious images were obtained even for a plate with complex geometries by taking an average of the images obtained at multiple frequencies.

A defect detection technique based on time-reversal concept is proposed to detect and locate the defects in a plate structure. Time-reversal imaging method is widely use as an advanced, robust data processing and imaging technique in structure health monitoring to detect the defects. Physically, the time reversed signal will retrace its original path precisely, which means that the signals will be refocused back on the source and defects after we record, time reverse and back propagate the wave signal experimentally or numerically. In this paper, a distributed actuator/sensor network is placed on a square homogeneous plate to generate and collect the wave signals in the plate. The time-reversal technique is then used to interpret the physical meaning of the recorded data and image the defects in the plate. Computer simulations are presented to illustrate the feasibility of the technique in this paper.

Crystalline materials exhibit long-range ordered lattice unit, within which resides nonperiodic structural features called defects. These crystallographic defects play a vital role in determining the physical and mechanical properties of a wide range of material systems. While computer vision has demonstrated success in recognizing feature patterns in images with well-defined contrast, automated identification of nanometer scale crystallographic defects in electron micrographs governed by complex contrast mechanisms is still a challenging task. Here, building upon an advanced defect imaging mode that offers high feature clarity, we introduce DefectSegNet - a new convolutional neural network (CNN) architecture that performs semantic segmentation of three common crystallographic defects in structural alloys: dislocation lines, precipitates and voids. Results from supervised training on a small set of high-quality defect images of steels show high pixel-wise accuracy across all three types of defects: 91.60 ± 1.77% on dislocations, 93.39 ± 1.00% on precipitates, and 98.85 ± 0.56% on voids. We discuss the sources of uncertainties in CNN prediction and the training data in terms of feature density, representation and homogeneity and their effects on deep learning performance. Further defect quantification using DefectSegNet prediction outperforms human expert average, presenting a promising new workflow for fast and statistically meaningful quantification of materials defects.

This paper focused on the light source optimization for visual inspection of piston surface defects. A novel structured lighting system was developed to overcome the difficulties in the well-qualified imaging of tiny and random defects on the cylindrical smooth surface of components such as pistons. A polarized light-filtering based method was proposed to enhance the defect image contrast, enlarge the detection range, and suppress the noise of flawless area. It was both experimentally proven and theoretically proven effective by mathematical modeling of light intensity loss during light propagation. To analyze the influence of the pose and position of light sources on defect imaging quality, the system model for camera, light source, and workpiece was established, and the structure parameters of the lighting system were optimized to improve the brightness uniformity over the entire inspection region and lighting efficiency. Moreover, a soft lighting method was introduced as a subsidiary means of removing the surface noise at two ends of a piston. This method was found to be more effective compared with conventional software filtering algorithm. Finally, a case was examined. The defects on the automotive brake master piston surface were captured using the optimized light source system. A random sampling experiment with 600 specimens revealed that the false-positive rate was about 2.3%, and with no leak detection. The findings have been applied in the production, and it is expected to be referred in inspecting defects on other smooth cylindrical surfaces.

The Lamb synthetic aperture focusing technique (L-SAFT) imaging algorithm in the Fourier domain is used to produce Lamb wave imaging in plates while considering the wave dispersive properties. This artificial focusing technique produces easy-to-interpret, modified B-scan type images of Lamb wave inspection results. The high level of sensitivity of Lamb waves combined with the L-SAFT algorithm allows one to detect and to produce images of corrosion defects with small depth-to-wavelength ratio. This paper briefly presents the formulated L-SAFT algorithm used for Lamb waves and, in more details, some experimental results obtained on simulated and real corrosion pits, demonstrating the benefit of combining L-SAFT with pulse-echo Lamb wave inspection. The obtained images of the real corrosion defects showed detection of pits with a depth-to-wavelength ratio of approximately 2/11.

Additive manufacturing has made it possible to easily create parts with complex shapes, even out of metal materials. However, in order to guarantee the quality of such parts, there is a need to establish a nondestructive inspection technique that is feasible for such complex structures. In this presentation, I will introduce a technology that can visualize internal damage even in complex objects by utilizing the ultrasonic field generated and diffused inside the object with non-contact manner. Ultrasonic waves generated by laser irradiation resonate with the natural frequency of defects such as delamination near the surface of an object. By scanning the laser beam for generating ultrasonic waves and detecting vibrations at a fixed position on the surface of the object, an image of defects in the vicinity of the surface can be obtained as a distribution of vibration energy. The distribution of vibration energy does not depend on reflected or scattered waves from the object's wall, but only on information from the point where the laser is irradiated. This technique is expected to be especially useful for in-situ inspections of the additive manufacturing objects.

Phase defect printability and imaging characteristics were investigated by using aerial image simulation to clarify the phase defect impact on patterns depending on defect types, and on exposure conditions. In particular, the difference between the impacts caused by the same size bump phase defect and pit phase defect on 28 nm ~ 16 nm L&S projected patterns were investigated by calculating line width variations. Aerial images of phase defects in an absence of any absorber pattern were also calculated, and the image intensity losses of the two types of defects were compared. For a dipole illumination with 0.25 NA (numerical aperture) the pit phase defect impact was found to be stronger than the bump phase defect impact, when the two defect widths were less than 70% of the half-pitch of L&S patterns on the mask. This occurrence was not foreseen by the defect image calculation. On the other hand, for circular illumination with 0.33 NA, the bump defect impact was found to be stronger than the pit phase defect impact, which was consistent with the defect image calculation results. The contribution of dipole illumination in lowering the phase defect impact was confirmed for both bump and pit phase defects.

A laboratory and theoretical study of the transition from strongly reflected surging to dissipative plunging breakers on a relatively steep plane beach (1:8) has revealed the following: (1) The run-up and offshore variation of sea surface elevation of surging waves are well predicted by linear theory. (2) The fluctuating part of the run-up (related to the amplitude of the reflected incident wave) reaches a maximum value; a further increase in incident progressive wave energy results in increased dissipation. (3) Subharmonic edge waves (the growing instabilities of surging waves) are driven primarily by the swash motion, which does not increase with increasing incident breaking wave height. However, the turbulence accompanying incident wave breaking, and the effective eddy viscosity, rapidly increases with increasing breaker height. As a result, subharmonic resonances do not occur with spilling or steep plunging waves; very strong viscous effects suppress the nonlinear instabilities. (4) edge waves generated by a surging incident wave can be suppressed by superimposing an additional breaking wave of different frequency on the incident wave field. Thus, any excited edge waves are likely to have length scales at least the order of a surf zone width.

This review discusses how the X-ray diffraction images of crystal lattice defects form and acquire structure when using X-ray topography methods. Approaches for describing (ray optics and wave optics) and application fields of the geometrical and diffraction optics of a real crystal are analyzed. Specific experimental images of dislocations and other defects are used as examples to demonstrate the role of various diffraction effects (wave reflection from lattice distortions, diffraction focusing, channeling) in determining the character of the image formed. The potential for obtaining quantitative information on defect parameters is discussed.

Ultrasonic guided waves have shown great potential for long range inspections of structures with large areas, such as pipes, vessels, rails, etc. The possibility of finding defects depends on whether scattered waves from a defect are detectable. For example, for a liquid‐filled pipeline inspection using torsional waves, the incident waves may be converted to longitudinal waves, which could then leak into the liquid and become undetectable. Therefore, the wave mode conversion study of a defect, especially a 3‐dimensional defect, becomes an interesting and valuable topic. The wave scattering and mode conversion of a through‐wall hole in a plate was studied both experimentally and theoretically. Mixed mode conversions from SH modes to Lamb modes were demonstrated utilizing electromagnetic acoustic transducer (EMAT) guided wave techniques and a hybrid 3‐D boundary element method. This mixed mode study could provide very useful guidance for guided wave inspection methodology. It is also very helpful in algorithm development for defect discrimination and sizing.

Topography is a main factor affecting ground motion. Theoretical investigations proved that it affects the arrival time, propagation energy, and waveform. Moreover, topography is also an important source to produce coda wave. It has been showed that the influence of complex topography on seismic waves not only depends on the spectral nature of seismic source, but also depends on the character of topographical scales. In this article, we simulated frequency responses of topography with multiple spatial scales due to incident SH wave by using local discrete wave‐number method, and found a resonance‐like relationship between the scales of topography and the frequency of incident wave. Such relationship underlies the explanation for the phenomena that frequency responses of topography depend on both topographical scale and frequency of incident wave. It is also useful in constructing the models for synthesizing seismograms. For example, we can ignore those spatial components of structural model whose contribution to the total seismic response is too small to be accounted, to achieve maximum computation efficiency.

Manganites are technologically important materials, used widely as solid oxide fuel cell cathodes; they have also been shown to exhibit electroresistance. Oxygen bulk diffusion and surface exchange processes are critical for catalytic action, and numerous studies of manganites have linked electroresistance to electrochemical oxygen migration. Direct imaging of individual oxygen defects is needed to underpin understanding of these important processes. Currently, it is not possible to collect the required images in bulk, but scanning tunnelling microscopy (STM) could provide such data for surfaces. Here, we report the first atomic resolution images of oxygen defects at a manganite surface. Our experiments also reveal defect dynamics, including oxygen adatom migration, vacancy-adatom recombination and adatom bistability. Beyond providing an experimental basis for testing models describing the microscopics of oxygen migration at transition-metal oxide interfaces, our work resolves the long-standing puzzle of why STM is more challenging for layered manganites than for cuprates.

A method combining Green's function retrieval theory and sign coherence factor (SCF) imaging is presented to detect near-surface defects in rails. The defects are close to the ultrasonic phased array and near-surface acoustic information of defects is obscured by the non-linear effects of the initial wave signal in directly acquired responses. To overcome this problem, cross-correlations of the diffuse field signals captured by the array transducer are performed to reconstruct the Green's function. SCF imaging is used to further improve the spatial resolution and signal-to-noise ratio (SNR) of near-surface defects in rails. Experiments are conducted on two rails containing two and four defects, respectively. The results show that these defects can be clearly identified when using the reconstructed Green's function. However, the images of near-surface defects are masked and cannot be distinguished when using directly captured signals and total focus imaging. The proposed method reduces the background noise and allows for effective imaging of near-surface defects in rails.