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

The non-contact measurement called scanning laser source (SLS) technique is applied to imaging inspection for subsurface delamination in a metal block and the effect of frequencies used for imaging is discussed with finite element method and experiments for an aluminum alloy block. First, FE formulation for the vibration of a closed structure described the relation between resonances in the whole structure and vibration distributions, and FE calculation provided the resonant frequencies and the resonant patterns of a metal block, which agreed well with experimental results. Next, images were obtained for a specimen with delamination using the SLS technique. When narrowband burst waves were used, the delamination images were largely different due to the resonances. For broadband chirp waves, the clear delamination images could be obtained in the frequency ranges including multiple resonant frequencies because diffuse fields were well established.

A structure for an underwater sound absorber with subwavelength thickness and a quasi-perfect absorption property at multiple frequency bands is reported. This absorber consists of a viscoelastic coating layer embedded with periodically distributed plate scatterers (PSs). The embedded PSs cannot only slow sound waves in the coating, leading to a down-shifted resonance frequency where the absorption is maximized, but also introduce multiple local bending modes and local longitudinal modes in the coating. Via proper selection of the parameters of the PSs and the PS array, multiple local resonance modes of different types in a coating unit can be excited, resulting in quasi-perfect absorption of incident sound at multiple frequencies whose wavelengths are much longer than the thickness of the coating layer. For example, absorption (89%) of underwater sound at 462.9 Hz is achieved by such a layer with a thickness of 6 cm, which is 1.9% of the wavelength of the incident sound. Broadband quasi-perfect absorption can also be realized by coupling of those multiple local resonant modes. This quasi-perfect absorption property can also be observed for sound waves with different incident angles, because a large number of local intrinsic modes could still be excited.

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.

The inelastic contribution to high resolution images of defects

Although cognitive functions are hypothesized to be mediated by synchronous neuronal interactions in multiple frequency bands among widely distributed cortical areas, we still lack a basic understanding of the distribution and task dependence of oscillatory activity across the cortical map. Here, we ask how the spectral and temporal properties of the local field potential (LFP) vary across the primate cerebral cortex, and how they are modulated during visual short-term memory. We measured the LFP from 55 cortical areas in two macaque monkeys while they performed a visual delayed match to sample task. Analysis of peak frequencies in the LFP power spectra reveals multiple discrete frequency bands between 3–80 Hz that differ between the two monkeys. The LFP power in each band, as well as the Sample Entropy, a measure of signal complexity, display distinct spatial gradients across the cortex, some of which correlate with reported spine counts in layer 3 pyramidal neurons. Cortical areas can be robustly decoded using a small number of spectral and temporal parameters, and significant task dependent increases and decreases in spectral power occur in all cortical areas. These findings reveal pronounced, widespread and spatially organized gradients in the spectral and temporal activity of cortical areas. Task-dependent changes in cortical activity are globally distributed, even for a simple cognitive task.

Guided wave techniques are expected to become an effective means for rapid, long-range inspection of pipes. Such techniques still have many practical difficulties in application, however, due to the complex characteristics of guided waves such as dispersion and their multimodal nature. A defect imaging technique is developed in this study to overcome the complexities of guided wave inspection. Received signals are separated into single-mode waveforms with a mode extraction technique and then spatial waveforms on the pipe surface at an arbitrary time are reconstructed. The predicted waveforms can provide a defect image at the moment when an incident wave arrives at a defect region, which is based on a time-reversal technique. This defect imaging technique is experimentally verified using eight signals detected at eight different circumferential positions. Images of artificial defects are obtained with one-hole and two-hole test pipes, and increasing the frequency of incident waves increases the resolution of the images. Holes and pipe ends are recognizable in the images, but the reconstructed images contain some errors in the area behind the defects where guided waves do not propagate or do not reflect back to the receiving transducers.

Recent findings in monkeys suggest that intrinsic periodic spiking activity in selective cortical areas occurs at timescales that follow a sensory or lower order-to-higher order processing hierarchy (Murray JD, Bernacchia A, Freedman DJ, Romo R, Wallis JD, Cai X, Padoa-Schioppa C, Pasternak T, Seo H, Lee D, Wang XJ. Nat Neurosci 17: 1661-1663, 2014). It has not yet been fully explored if a similar timescale hierarchy is present in humans. Additionally, these measures in the monkey studies have not addressed findings that rhythmic activity within a brain area can occur at multiple frequencies. In this study we investigate in humans if regions may be biased toward particular frequencies of intrinsic activity and if a full cortical mapping still reveals an organization that follows this hierarchy. We examined the spectral power in multiple frequency bands (0.5-150 Hz) from task-independent data using magnetoencephalography (MEG). We compared standardized power across bands to find regional frequency biases. Our results demonstrate a mix of lower and higher frequency biases across sensory and higher order regions. Thus they suggest a more complex cortical organization that does not simply follow this hierarchy. Additionally, some regions do not display a bias for a single band, and a data-driven clustering analysis reveals a regional organization with high standardized power in multiple bands. Specifically, theta and beta are both high in dorsal frontal cortex, whereas delta and gamma are high in ventral frontal cortex and temporal cortex. Occipital and parietal regions are biased more narrowly toward alpha power, and ventral temporal lobe displays specific biases toward gamma. Thus intrinsic rhythmic neural activity displays a regional organization but one that is not necessarily hierarchical.NEW & NOTEWORTHY The organization of rhythmic neural activity is not well understood. Whereas it has been postulated that rhythms are organized in a hierarchical manner across brain regions, our novel analysis allows comparison of full cortical maps across different frequency bands, which demonstrate that the rhythmic organization is more complex. Additionally, data-driven methods show that rhythms of multiple frequencies or timescales occur within a particular region and that this nonhierarchical organization is widespread.

In order to more accurately grasp the exact shape, contour size and distribution of defects in the plate-like structures material and other detailed feature information, this paper designed the graphical user interface GUIGWT0.1, which is specifically used for ultrasonic guided wave imaging. This software integrates filtering back projection algorithm, damage probability reconstruction algorithm and diffraction tomography algorithm, which can image the plate-like structures structure as required, and develop the defect detection results to the visual direction. To investigate the validity of the interface, the projection data of lamb wave in the plate-like with a partial-thickness notch are numerically simulated by three-dimensional elastodynamic finite integration technique (EFIT). The resulting projected data is imported into the graphical user interface for imaging. For each existing reconstruction imaging, the result can be represented in terms of grayscale image of projected data, defect imaging, image color inversion and false color defect recognition. Through simple operation, reconstruction of image with defect of plate-like structure are obtained in the user interface.

Neural oscillations are fundamental for brain function and govern various cognitive processes. Recent functional magnetic resonance imaging advances offer the opportunity to study frequency-specific properties of blood-oxygen-level-dependent oscillations at multiple frequency bands. However, most have focused on spontaneous brain activity in the resting state, leaving a gap in direct evidence regarding the specific activations of cognitive tasks across different frequency bands. We aim to address this gap by exploring the role of blood-oxygen-level-dependent oscillations across multiple frequency bands in cognitive processes. We used task-functional magnetic resonance imaging data of 339 healthy young adults from the Human Connectome Project to map the activation patterns of performing seven cognitive tasks at multiple frequency bands (ie slow-1 to slow-6). Our findings revealed that different frequency bands are associated with distinct task-activation patterns. Specifically, slow-1/2/3 oscillations primarily contribute to local sensory information processing, while slow-4 is crucial for various fundamental cognitive functions. Slow-5 is involved in cognitive processes that require greater memory load, integrated cognitive processing, and attention maintenance. This underscores the importance of analyzing a broad frequency range to capture the full spectrum of cognitive function, highlighting the diverse roles of different frequency bands in brain activity, shedding light on the underlying mechanism of brain–behavior associations.

In this paper, we investigate wireless-powered communication system (WPCS) with multiple frequency bands. When ambient RF signals can be used as an only energy source of wireless devices (WDs), a traditional signal-generator-based communication (SGC) might be demanding due to its high power consumption mainly because of RF-chain, so that backscatter communication (BC) has gained much attention recently. However, the bandwidth efficiency of BC is significantly limited, and thus BC is not always the best option for WPCSs. Thus, we analyze this trade-off by comparing their achievable capacity and show conditions in which the throughput of SGC is higher than BC when multiple frequency bands are available as an energy source and communication channel. Based on the analyses, we propose a hybrid approach with SGC and BC, which enables WDs to decide the best frequency band and communication method in a distributed manner.

This paper presents a theory for broad-band matching of stripline junction circulators for operation in two or more frequency bands. In this theory it is assumed that the matching network is composed of cascaded transmission line transformers each of which is an odd multiple of a quarter-wavelength at the center frequencies. The conditions for simultaneous Chebyshev response in multiple frequency bands are determined, and it is investigated to what extent these conditions can be satisfied by stripline circulator junctions. Thus by using a first-order theory, it is shown that if a circulator junction, adjusted for double frequency operation, is matched for Chebyshev response by a transformer of proper length around one of the circulation frequencies then it is also matched for Chebyshev response around the other circulation frequency, provided that the same operation mode is used above and below material resonance. A routine for broad-band multiple frequency matching is proposed for junctions where Chebyshev response is not obtainable. Finally the properties of some externally matched circulators designed according to the theories are shown.

For clinical applications in epilepsy, magnetoencephalography (MEG) has been mostly used to localize sources of interictal spike activity using the single equivalent current dipole (ECD) method. Thanks to the advancement of analytical methodology for MEG signals, multiple frequency band signals, especially fast oscillations (>30 Hz), are now being used for localization of ictal and interictal epileptic activity in addition to the ECD method. Moreover, connectivity and network analysis utilizing multiple frequency band MEG signals have recently been adopted in the field of epilepsy. This chapter provides an overview of the clinical applications of multiple frequency band signal analysis in epilepsy for the purpose of localization of epileptiform activity sources and assessment of functional connectivity.

Understanding user-induced effects on signal reception across multiple frequency bands is of great scientific and military importance to the wireless industry. Various onbody locations and directional heading of the user are believed to impact the performance of mobile devices, but there has been little work across multiple frequency bands to quantify these user-induced effects. In this work, we perform a measurement study to explore user effects on radio wave propagation with varying line-of-sight conditions and environments across multiple frequency bands, including white space (500 and 800 MHz), cellular (1800 MHz), and WiFi (2400 MHz) frequency bands. To do so, we first conduct a baseline experiment that characterizes the propagation channel in this environment. We show that the propagation differences for ground-to-ground communication (common in Ad Hoc and WiFi scenarios) and tower-to-ground communication (common in cellular scenarios) are frequency dependent. Then, we measure signal quality as a function of the on-body location of the receiver, directional heading of the user with respect to the transmitter, vegetation type, frequency band, and propagation distance. Our assessment reveals that the user directionality with respect to the transmitter can reduce received signal strength up to 20 dB and reduce throughput by 20.9% at most. We also find that the body can act like an antenna, increasing reception by 4.4 dB and throughput by 14.4% over a reference node at the same distance. Since our study spans many critical (UHF) frequency bands, we believe these results will have far-reaching impact on a broad range of network types.

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.