Non-contact Manner Research Articles

Manufacturing of thermoplastic composite sandwich panels using induction welding under vacuum

A new method to manufacture thermoplastic composite sandwich panels is presented, making use of the induction welding process in which a magnetic susceptor generates the heat at the core/facesheet interface. This technique proposes a fast way to assemble thermoplastic sandwich structures without risking the deconsolidation of the composites skin. The welding pressure is obtained by applying vacuum over the sandwich panel. This vacuum induction welding method (Vac-IW) allows joining thermoplastic composite facesheets to a thermoplastic polymer core in a clean and non-contact manner. The feasibility of the method is demonstrated by preparing sandwich samples made of glass fibre reinforced polyetheretherketone (PEEK) skins and a 3D-printed polyetherimide (PEI) honeycomb core. A susceptor made of PEI and µm-sized nickel (Ni) particles is used to generate heat by magnetic hysteresis losses. The strength of the sandwich samples assembled by the Vac-IW method is evaluated by flatwise tensile (FWT) tests.

Acoustoelastic characterization of aluminum plates using zero group velocity Lamb modes

Acoustoelasticity, a characteristic of material anharmonicity, gives rise to a link between wave propagation velocity and the stress state in materials. Ultrasonic techniques to monitor this coupling, particularly with high sensitivity and in a noncontact manner, can have widespread application both in the quantification of applied and residual stress and in the characterization of nonlinear material behavior through measurement of higher order elastic constants. Here, we use a laser ultrasonic technique to excite and detect zero group velocity (ZGV) Lamb wave resonances in aluminum plates under uniaxial loading. A laser line source is used to excite these resonances at different orientations with respect to the applied load and the signals are detected using an interferometer. The effects of stress and source orientation on ZGV resonance frequencies are validated using the theory of acoustoelastic Lamb wave propagation. In addition, a model-based inversion technique is used to extract Murnaghan’s third-order elastic constants from measurements of the stress dependence of the first two ZGV modes generated parallel and perpendicular to the applied load. Laser generation and detection of ZGV resonances is shown to be an effective and powerful approach for the noncontact and nondestructive acoustoelastic characterization of elastic waveguides.

Papiliotrema flavescens, a plant growth-promoting fungus, alters root system architecture and induces systemic resistance through its volatile organic compounds in Arabidopsis

The current trend in agricultural development is the establishment of sustainable agricultural systems. This involves utilizing and implementing eco-friendly biofertilizers and biocontrol agents as alternatives to conventional fertilizers and pesticides. A plant growth-promoting fungal strain, that could alter root system architecture and promote the growth of Arabidopsis seedlings in a non-contact manner by releasing volatile organic compounds (VOCs) was isolated in this study. 26S rDNA sequencing revealed that the strain was a yeast-like fungus, Papiliotrema flavescens. Analysis of plant growth-promoting traits revealed that the fungus could produce indole-3-acetic acid and ammonia and fix nitrogen. Transcriptome analysis in combination with inhibitor experiments revealed that P. flavescens VOCs triggered metabolic alterations, promoted auxin accumulation and distribution in the roots, and coordinated ethylene signaling, thus inhibiting primary root elongation and inducing lateral root formation in Arabidopsis. Additionally, transcriptome analysis and fungal infection experiments confirmed that pretreatment with P. flavescens stimulated the defense response of Arabidopsis to boost its resistance to the pathogenic fungus Botrytis cinerea. Solid-phase microextraction, which was followed by gas chromatography-mass spectrometry analysis, identified three VOCs (acetoin, naphthalene and indole) with significant plant growth-promoting attributes. Their roles were confirmed using further pharmacological experiments and upregulated expression of auxin- and ethylene-related genes. Our study serves as an essential reference for utilizing P. flavescens as a potential biological fertilizer and biocontrol agent.

Acoustoelastic characterization of plates using zero group velocity Lamb modes

Acoustoelasticity, a characteristic of material anharmonicity, gives rise to a link between wave propagation velocity and the stress state in materials. Ultrasonic techniques to monitor this coupling, particularly with high sensitivity and in a noncontact manner, can have widespread application both in the quantification of applied and residual stress and in the characterization of nonlinear material behavior through measurement of higher order elastic constants. Here, we use a laser ultrasonic technique to excite and detect zero group velocity (ZGV) Lamb wave resonances in aluminum plates under uniaxial loading. A laser line source is used to excite these resonances at different orientations with respect to the applied load, and the signals are detected using an interferometer. The effects of stress and source orientation on ZGV resonance frequencies are validated using the theory of acoustoelastic Lamb wave propagation. In addition, a model-based inversion technique is used to extract Murnaghan's third-order elastic constants from measurements of the stress dependence of the first two ZGV modes generated parallel and perpendicular to the applied load. Laser generation and detection of ZGV resonances is shown to be an effective and powerful approach for the noncontact and nondestructive acoustoelastic characterization of elastic waveguides.

Relation between quadrupole ultrasonic resonance and shear viscoelasticity of polymer droplets with different glass transition temperatures

Abstract When observing the ultrasonic signal transmitted through a suspension of particles dispersed in a liquid, a peak is observed in the frequency spectrum of the attenuation coefficient of the ultrasonic energy. This peak mainly reflects shear elasticity, even though longitudinal ultrasound is used. Hence, the shear modulus of a single particle dispersed in a liquid can be obtained in a non-contact manner. In this study, we used ultrasound to analyze the process of polymer particle formation from an oil-in-water emulsion, in which a polymer solution containing an organic solvent is used as the oil phase, and the organic solvent is evaporated in water. Furthermore, the liquid-to-solid transition was quantified for microparticles consisting of various polymeric materials (liquid, rubber, and glass), and the relationship between the glass transition temperature, peak behavior of ultrasonic attenuation coefficient, and shear modulus was clarified.

Terahertz nondestructive stratigraphic reconstruction of paper stacks based on adaptive sparse deconvolution

Characterizing the number of sheets in a stack of paper typically involves mechanical separation of the individual sheets. Here, we explore an nondestructive method that can be applied to the intact paper stack. Namely, terahertz time-of-flight tomography, together with post signal-processing technique sparse deconvolution based on a two-step iterative shrinkage-thresholding algorithm (SD/TWIST), is employed to reconstruct the stratigraphy of stacks of sheets of paper with multilayered structure in a nondestructive and noncontact manner. The double-Gaussian mixture model (DGMM) is also incorporated to suppress dispersion in the reflected THz echoes. The effectiveness and accuracy of the proposed adaptive sparse-deconvolution method are verified experimentally and numerically. Compared with the commonly used frequency wavelet-domain deconvolution (FWDD) method and previous implementations of sparse deconvolution based on an iterative-shrinkage and thresholding algorithm (SD/IST), the proposed sparse-deconvolution approach can provide a clearer and rapid stratigraphic reconstruction of the paper stacks studied, while ensuring accurate thickness information for each paper sheet in the presence of noise, revealing the potential usage of real-time THz tomographic-image processing.

Polarization modulation scanning optical microscopy method

Since the discovery of monolayer graphene, the novel physical properties of two-dimensional (2D) materials, particularly those with fewer layers that often exhibit unique properties different from bulk materials, have received significant attention. Therefore, accurately determining the layer number or obtaining the microscopic surface morphology is crucial in the laboratory fabrication and during device manufacturing. However, traditional detection methods have numerous drawbacks. There is an urgent need for a convenient, accurate, and non-destructive scientific method to characterize the layer number and surface microstructure of 2D materials. By combining the experimental setup of laser scanning photocurrent spectroscopy, we develop a polarization-modulated scanning optical microscope based on the principle of reflectance difference spectroscopy. By monitoring the reflectivity of the samples, we can observe changes in the reflection signal strength of MoS<sub>2</sub> with different layer numbers. The intensity of the reflectance differential spectral signal reflects changes in the layer count within the sample. We can characterize the changes in the number of layers of 2D materials in a non-contact manner by using polarization-modulated scanning optical microscopy. Through the study of the reflectance differential spectra of two typical 2D layered materials, MoS<sub>2</sub> and ReSe<sub>2</sub>, we find that our polarization-modulated scanning optical microscope system is also more sensitive to the characteristics of the stacking anisotropy of the 2D materials than the conventional reflection microscope. This indicates that our research contributes to a better understanding of the layer number characteristics and anisotropic properties of layered 2D materials. Furthermore, our research also provides a non-contact optical method to characterize the number of layers and optical anisotropy of two-dimensional layered material.

Non-Contact Measurement of Cardiopulmonary Activity Using Software Defined Radios.

Vital signs are important indicators to evaluate the health status of patients. Channel state information (CSI) can sense the displacement of the chest wall caused by cardiorespiratory activity in a non-contact manner. Due to the influence of clutter, DC components, and respiratory harmonics, it is difficult to detect reliable heartbeat signals. To address this problem, this paper proposes a robust and novel method for simultaneously extracting breath and heartbeat signals using software defined radios (SDR). Specifically, we model and analyze the signal and propose singular value decomposition (SVD)-based clutter suppression method to enhance the vital sign signals. The DC is estimated and compensated by the circle fitting method. Then, the heartbeat signal and respiratory signal are obtained by the modified variational modal decomposition (VMD). The experimental results demonstrate that the proposed method can accurately separate the respiratory signal and the heartbeat signal from the filtered signal. The Bland-Altman analysis shows that the proposed system is in good agreement with the medical sensors. In addition, the proposed system can accurately measure the heart rate variability (HRV) within 0.5m. In summary, our system can be used as a preferred contactless alternative to traditional contact medical sensors, which can provide advanced patient-centered healthcare solutions.

Flow-controlled air-jet for in vivo quasi steady-state and dynamic elastography with MHz optical coherence tomography.

Optical coherence elastography (OCE) has been introduced for several medical applications to determine tissue mechanical parameters. However, in order to measure sensitive healthy tissue like brain in vivo, the excitation force needs to be carefully controlled and as low as possible (under 100 μN). Preferably, the excitation should be applied in a non-contact manner. In this work, an air-jet excitation source for this specific purpose has been developed and characterized. The design focus was set on the exact measurement and control of the generated excitation force to better comply with in vivo medical safety requirements during surgery. Therefore, an excitation force control and measurement system based on the applied gas flow was developed. This system can generate short, high dynamic air-puffs lasting fewer than 5 ms, as well as quasi-static excitation forces lasting 700 ms. The force range covers 1μN to 40 mN with a force error margin between 0.1% and 16% in the relevant range. The excitation source, in conjunction with a 3.2 MHz optical coherence system, enables phase-based, dynamic, and quasi steady-state elastography, as well as robust non-contact classical indentation measurements. The presented system is a preliminary prototype intended for further development into a clinical version to be used in situ during brain tumor surgery.

Mid-infrared passive spectroscopic imaging for visualizing tooth quality.

Although the measurement of tooth quality is necessary for precise prediction of caries formation, typical measurement methods include tooth-hardness measurements and absorption spectroscopy, which generally use infrared light irradiation. These methods are destructive or invasive, and obtaining two-dimensional information in the oral cavity is difficult. Mid-infrared emissions from the surface of an object reflect intrinsic vibrations of molecules in the object. In this study, a mid-infrared passive spectroscopic imaging system was developed using an inexpensive uncooled microbolometer array sensor with an optimized multi-slit, which eliminated the cancellation of interference intensities between two adjacent emission points, to obtain two-dimensional information from an object without external infrared light irradiation. First, the feasibility of obtaining two-dimensional information on tooth quality using the proposed system was examined, and emission spectra attributed to phosphate ions in hydroxyapatite (HAp), the main component of enamel, were successfully obtained from bovine teeth. Further, the hardness of bovine teeth was measured, and a correlation (R2 = 0.8067) between the Vickers hardness and peak area ratio of phosphate ions assigned to the crystalline and amorphous phases of a tooth was established. Additionally, tooth-hardness visualization in a non-contact manner was demonstrated as two-dimensional information using the obtained regression equation.

Numerical Beamforming and Parametric Descriptions of Laguerre-Gaussian Vortex Beams

Vortex beams are beams with a helical wavefront that have found applications in optical or acoustic tweezers to manipulate microscopic particles. Vortex beam imposes torque or force to particles, allowing them to trap the object within the beam's field and induce motion or displacement in a non-contact manner. One type of such beam is a Laguerre-Gaussian beam, where the solution of a Gaussian wave is modified by the Laguerre polynomial term that determines the pattern and helical characteristic of the beam. In this paper, a numerical method based on the mathematical expression of the Laguerre-Gaussian beam is implemented to describe how the parameters change the physical behavior of the beam. This work has shown that a straightforward numerical method is capable of producing this kind of beam. Therefore, this approach can be used for generating vortex beams for physical emissions, complex numerical simulations, or demonstrations for teaching purposes

A dynamic obstacle avoidance method for collaborative robots based on trajectory optimization

Background Collision detection is crucial in the design of robot planning algorithms. Efficient distance sensors can provide high-resolution environmental collision information to the robot's planning algorithm. However, this also leads to the robot obstacle avoidance performance being limited by the performance of the sensors. Therefore, it becomes a challenge to achieve efficient obstacle avoidance with low-resolution environmental information. Methods First, we use a self-developed capacitive array non-contact distance sensing flexible surface for sensing the proximity of colliding objects. Second, we designed an optimization-based dynamic obstacle avoidance planning algorithm, using only the minimum separation distance and penetration direction as obstacle avoidance information, and referring to the idea of stochastic gradient descent, using real-time collision avoidance information to do single-step optimization adjustment. Results We conducted the dynamic obstacle avoidance test experiment by connecting the electronic skin to the semi-physical prototype and the full physical prototype. The experiments show that efficient dynamic obstacle avoidance can be realized under the maximum effective range of only 5~7cm, and it has strong flexibility to avoid different shapes of dynamic obstacles in a non-contact manner, and finally arrive at the target position. Conclusions In this paper, an online obstacle avoidance planning algorithm designed based on an optimization method that is not limited to the shape of obstacles is proposed, and the effectiveness of the algorithm is verified by physical experiments in combination with a self-developed flexible distance sensing surface. It is of great significance for the safe operation of human-robot interaction in collaborative robots.

Investigation the feasibility of complex circular motion of implants in magnetic stereotaxis systems

In this paper, we explore the feasibility of controlling the circular motion of the implant in a non-contact manner by controlling the change of the external magnetic field in a magnetic stereotaxic system. The change of the external magnetic field was simulated through computer simulation experiments, so as to control the circular motion of a small permanent magnet in a non-contact manner, and in the actual experiment, the slide rail system was equipped with a large permanent magnet to form an external magnetic field, and the operation of the slide rail system was controlled by an Arduino microcontroller. The results of computer simulation experiments were verified, and the feasibility of non-contact control of the circular motion of the implant was clarified.

Ultrafast THz probing of nonlocal orbital current in transverse multilayer metallic heterostructures

THz generation from femtosecond photoexcited spintronic heterostructures has become a versatile tool for investigating ultrafast spin-transport and transient charge-current in a non-contact and non-invasive manner. The equivalent effect from the orbital degree of freedom is still in the primitive stage. Here, we experimentally demonstrate orbital-to-charge current conversion in metallic heterostructures, consisting of a ferromagnetic layer adjacent to either a light or a heavy metal layer, through detection of the emitted THz pulses. Our temperature-dependent experiments help to disentangle the orbital and spin components that are manifested in the respective Hall-conductivities, contributing to THz emission. NiFe/Nb shows the strongest inverse orbital Hall effect with an experimentally extracted value of effective intrinsic Hall-conductivity, (σSOHint)eff~195Ω−1cm−1\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${({\\sigma }_{{SOH}}^{{{{{\\mathrm{int}}}}}})}^{{eff}} \\sim 195{\\varOmega }^{-1}{{cm}}^{-1}$$\\end{document}, while CoFeB/Pt shows maximum contribution from the inverse spin Hall effect. In addition, we observe a nearly ten-fold enhancement in the THz emission due to pronounced orbital-transport in W-insertion heavy metal layer in CoFeB/W/Ta heterostructure as compared to CoFeB/Ta bilayer counterpart.

GOL-SFSTS based few-shot learning mechanical anomaly detection using multi-channel audio signal

Anomaly detection has become an essential component of mechanical equipment preventive maintenance. When encountered in complicated industrial and military applications, audio signals can be captured in a non-contact manner, preserving significant engineering potential. Common systems that operate on single-channel raw sound inputs have limited anti-noise capabilities and few-shot learning (FSL) robustness. This study proposed a competitive FSL multi-channel anomaly detection framework that uses the global optimization layer-based spallation few-shot training strategy (GOL-SFSTS) on audio Mel-spectrogram samples. The transform on 8-channel audio Mel Spectrogram increases the model's feature capture ability for multi-channel signals greatly. A 'hot-plug' discrepancy distance operator GOL is used to improve the model's anti-noise capacity when dealing with real-world operating situations. SFSTS is a growable learning approach designed to make the model more suitable for later classes and to increase FSL compatibility. We conduct ablation comparisons with other cutting-edge techniques, and FSL classification results on MIMII datasets show that our framework outperforms ResNet34 in full, 30-shot, 15-shot, and 5-shot by 9.6 %, 10.4 %, 9.8 %, and 5 %, respectively. The results of four trials indicate that the designed GOL-SFSTS framework is effective for anomaly detection applications. This paper's impressive achievements have opened up new opportunities for FSL multi-channel audio mechanical anomaly detection.

Identifying leather type and authenticity by optical coherence tomography

PurposeThis study aims to identify leather type and authenticity through optical coherence tomography.Design/methodology/approachOptical coherence tomography images taken from genuine and faux leather samples were used to create an image dataset, and automated machine learning algorithms were also used to distinguish leather types.FindingsThe optical coherence tomography scan results in a different image based on leather type. This information was used to determine the leather type correctly by optical coherence tomography and automatic machine learning algorithms. Please note that this system also recognized whether the leather was genuine or synthetic. Hence, this demonstrates that optical coherence tomography and automatic machine learning can be used to distinguish leather type and determine whether it is genuine.Originality/valueFor the first time to the best of the authors' knowledge, spectral-domain optical coherence tomography and automated machine learning algorithms were applied to identify leather authenticity in a noncontact and non-invasive manner. Since this model runs online, it can readily be employed in automated quality monitoring systems in the leather industry. With recent technological progress, optical coherence tomography combined with automated machine learning algorithms will be used more frequently in automatic authentication and identification systems.

Deep feature interactive network for machinery fault diagnosis using multi-source heterogeneous data

Infrared thermal images have been applied for monitoring health condition of machines due to the noncontact and nonintrusive manner. While fault diagnosis performance of those deep neural networks (DNNs) that use infrared thermal images is restricted by the information learned from single sensor. In this study, multi-source heterogeneous data (i.e., infrared thermal images and vibration signals) are used for machinery fault diagnosis. A new DNN, i.e., deep feature interactive network (DFINet) is proposed for machinery fault diagnosis, where a novel interactive feature extraction module is developed for adaptive feature fusion on multi-source heterogeneous data. Firstly, the private and public features of multi-source heterogeneous data are extracted separately by measuring the distribution discrepancy between heterogeneous features in the feature interactive module. The feature splicing is implemented to interactively fuse common fault features of heterogeneous data and to preserve private unique features. A global feature fusion module is further proposed for adaptive fusion of superficial local features and deep abstract features learned by different feature interactive modules. The experimental results on a rotor test-bed and gearbox test-bed indicate that DFINet is promising for fusion and feature extraction on multi-source heterogeneous data in machinery fault diagnosis.

Ultrafast terahertz spin and orbital transport in magnetic/nonmagnetic multilayer heterostructures and a perspective

Ultrafast optically excited ferromagnetic (FM)/nonmagnetic (NM) multilayer heterostructures have been demonstrated recently as efficient, high-power, and broadband sources of terahertz (THz) electromagnetic radiation. Since these spintronic THz emitters exploit the conversion from ultrafast spin to charge current, either in bulk or at the interface, the THz pulses inhere all the characteristics of the involved mechanisms and dynamics associated with spin-charge interconversion processes. Deconvolving the same requires meticulous and careful experimentation and analysis. In this article, we review the current state-of-the-art in this field and provide a perspective on the emerging phenomena, which are prospering as new research avenues and demonstrate application potential for futuristic THz technologies. In the process of developing efficient spintronic THz emitters by optimizing various conditions including those with material parameters and excitation light, it turns out that THz emission spectroscopy itself can be a unique experimental tool for probing microscopic dynamical magnetic and spintronic effects, induced by femtosecond laser pulse excitation, in a noncontact and noninvasive manner. Several breakthroughs can be listed from the literature in this regard from the last decade. Just recently, ultrafast orbitronics is another dimension that is taking shape and will impact the field immensely. A fair account to this topic is also presented in the article.

Practical Implementation of Motion-Robust Radar Imaging and Whole-Body Weapon Detection for Walk-Through Security Screening

Radar-based sensing and concealed weapon detection technologies have been attracting attention as a measure to enhance security screening in public facilities and various venues. For these applications, the security check must be performed without impeding the flow of people, with minimum human effort, and in a non-contact manner. We developed technologies for a high-throughput walk-through security screening called Invisible Sensing (IVS) and implemented them in a prototype system. The IVS system consists of dual planar radar panels facing each other and carries out an inspection based on a multi-region screening approach as a person walks between the panels. Our imaging technology constructs a high-quality radar image that compensates for motion blur caused by a person's walk. Our detection technology takes multi-view projected images across the multiple regions as input to enable real-time whole-body screening. The IVS system runs its functions by pipeline processing to achieve real-time screening operation. This paper presents our IVS system along with these key technologies and demonstrates its empirical performance.

A non-contact interactive system for multimodal surgical robots based on LeapMotion and visual tags.

In recent years, the integration of robots in minimally invasive surgery has gained significant traction in clinical practice. However, conventional contact-based human-computer interaction poses the risk of bacterial infection, significantly limiting the role of robots in surgery. To address this limitation, we propose an innovative interaction method rooted in gestures and visual tags, allowing surgeons to control and fine-tune surgical robots without physical contact with the environment. By encoding the six gestures collected using LeapMotion, we can effectively control the surgical robot in a non-contact manner. Moreover, utilizing Aruco technology, we have accurately identified the 3D spatial position of the visual label, and developed 12 fine-tuning operations to refine surgical instruments. To evaluate the applicability of our proposed system in surgery, we designed a relevant experimental setup. In the experiment, we achieved enough precision. These results demonstrate that our system meets the clinical standard, providing doctors with a non-contact and flexible means of interacting with robots during surgery.