The physical characteristics of gas-solid triboelectric charging under high-speed flows remain poorly understood due to limited direct experimental evidence. In this study, in situ triboelectric current measurements were conducted on a metallic blunt body in a shock-wave wind tunnel. The current signals change from random-like fluctuations at Ma3 to intermittent high-amplitude events at Ma6, and further to amplitude-modulated, non-stationary behavior at Ma8. Statistical analysis and continuous wavelet transform were used to analyze the signal features. The triboelectric current is interpreted as a macroscopic response of stochastic micro-contact events, indicating a transition in the temporal characteristics of the current with increasing inflow velocity, and providing experimental support for mechanistic interpretation of high-speed gas-solid friction.

To address the issue of significant distribution shifts in transmission systems under cross-speed and cross-load operating conditions, which leads to a decline in the generalization performance of fault diagnosis models under unknown conditions, a novel time-frequency adaptive domain generalization framework of TFAR-UDP is proposed. Firstly, the time-frequency adaptive receptive field network (TFAR-Net) is designed, integrating time-frequency decoupled isotropic convolutions, adaptive multi-scale hollow convolutions and band-specific attention mechanisms to achieve joint modeling of fault impulse evolution, resonance band responses and multi-scale time-frequency textures. Secondly, the proposed unified dual-path (UDP) perturbation strategy, which utilizes EFDM spatial-domain ordering statistical perturbations and Fourier frequency-domain amplitude spectral perturbations to expand the source domain sample space from both spatial statistical distribution and spectral distribution perspectives, whilst employing a co-variance uncertainty weighting mechanism to adaptively coordinate the dual-path optimization process. To validate the effectiveness of the proposed, a system-level fault diagnosis task comprising key components such as bearings, gears, rotors and motors is constructed, and cross-speed and cross-load generalization experiments are conducted on the self-built XUST-IDC dataset and the publicly available BJTU-RAO dataset. The results show that TFAR-UDP achieves average accuracy rates of 92.11% and 81.08% in cross-speed and cross-load experiments on the XUST-IDC dataset, respectively; on the BJTU-RAO dataset, 84.83% and 93.83%, respectively, outperforming mainstream domain-specific generalization methods. The results validate the effectiveness and robustness of the proposed in fault diagnosis across operating conditions for transmission systems.

The interaction between the vehicle's electrostatic accumulation and the plasma in hypersonic flight environments has received little attention. To investigate this mechanism, an inductively coupled plasma (ICP) system was employed to generate plasmas with plasma densities up to 1017m-3 and electron temperatures of several eV, replicating key characteristics of hypersonic plasmas. Using this platform, the interactions of metallic and dielectric targets with the plasma were systematically examined. The results show that positively charged metallic targets significantly enhance local plasma density by up to 180% via electrostatic attraction. However, negatively charged metallic targets reduced plasma density due to electric field repulsion, followed by a subsequent increase attributed to secondary electron emission from positive ion bombardment. The motion of charged particles induced measurable currents at the milliampere level in the circuit. In contrast, dielectric targets accumulate surface charge that effectively suppresses electric-field penetration and produces negligible influence on the adjacent plasma. These observations illustrate how electrostatic potentials modify the dynamics of charged-particle near different materials and provide useful guidance for electrostatic protection and flight safety considerations in hypersonic vehicles.

The charge quantity is a fundamental physical parameter that reflects the electrical state of an object. Accurately estimating the charge of an object facilitates the assessment of electrostatic discharge risks and aids in preventing accidents. Measuring the charge of a moving object has long posed a technical challenge in this field. This paper proposes a non-contact method for estimating the charge of a moving object by utilizing the electrostatic signals generated by the object’s motion and its motion data. First, a non-contact charge measurement model based on a mutual capacitance matrix was developed using the image charge method in electrostatics. The accuracy of the model was verified through simulations of the charge on the sensing electrode. Next, a correction method for charge calculation was further proposed to reduce measurement errors caused by parasitic capacitance from the experimental setup. Finally, a verification experiment was conducted, wherein an electrometer measured the charge of the object in a stationary state, providing a reference to validate the proposed method. The experimental results demonstrated a strong correlation (r > 0.96) and consistency (within the 95% confidence interval) between the measured and reference values across various conditions. The absolute error of the measurements was within ±1 nC (mean ± standard deviation: -0.04 ± 0.4 nC), with a relative error of approximately ±10%. This study contributes to the prevention of electrostatic discharge accidents involving moving objects and presents novel insights and technological approaches for electrostatic detection.

Pulsed discharge in water is an indispensable method to carry out laboratory simulation of underwater explosion effects and bubble dynamics research, which has attracted more and more attention in recent years. In this paper, discharge characteristics and spatial-temporal evolution behavior of underwater bubbles in needle-needle pulsed discharge and electric explosion of a fine copper wire ( $50\ \mu\mathrm{m}$ in diameter) are compared in detail. High-speed photography and electrophysical diagnostics are applied to characterize dynamic processes. The results indicate that under the condition of 4 J stored energy, the deposition energy of underwater electrical wire explosion can reach 3.83 J (>95 %), which is 10 times higher than that of pulsed discharge under similar stored energy. The peak electric power of electrical wire explosion is 22.65 MW, which is two orders of magnitude higher than the pulsed discharge. Compared with the underwater pulsed discharge, the bubble diameter produced by the underwater electrical wire explosion is larger (the length of copper wire is 1 cm, the maximum diameter of the bubble is 2.64 cm), the expansion rate is faster, and the duration is longer. The bubble morphology generated by underwater pulsed discharge is irregular and influenced by the randomly-developed streamers, whereas the bubble generated by underwater electrical wire explosion exhibits obvious shock wave, explicit gas-liquid boundary, and typical cylindrical-spherical evolution process, close to the case of underwater explosion. In addition, for copper wire electric explosion, the larger the stored energy, the larger the bubble radius and the longer the duration.

Lightning discharge between the thundercloud and the sea surface is a gas-liquid interface discharge, accompanied by intense electromagnetic radiation, causing severe interference to underwater electromagnetic equipment. Elucidating the electromagnetic radiation characteristics during lighting discharge has practical significance for optimizing the anti-interference capacity of underwater electromagnetic equipment. In this paper, a liquid interface pulsed discharge system was constructed, simulating the lightning discharge on seawater through the application of a kA-level pulse current. The electromagnetic radiation signals (within 200 MHz band), electrical parameters, and the space-time evolution of plasma during the discharge process were obtained through a combined diagnosis system, and the time and frequency domain analysis was carried out. The results indicate that the electromagnetic radiation during the interface discharge correspond to three stages: (I) application of pulse current, (II) partial discharge, (III) plasma development. Under different solution conductivities and different diameters of the induction wire, the electromagnetic radiation has stable spectral characteristics, showing distinct stripe regions, located around 115 MHz, 128 MHz, and 145 MHz, respectively. Such characteristic spectrum is of great significance for further research and applications.

This paper explores the aerodynamic characteristics of the He plasma jet under nanosecond pulse needle-ring discharge excitation (dielectric-barrier), and the influence of typical pulse parameters on the flow field is preliminarily ascertained. Schlieren photography is employed to visualize the flow field of the jet, and dynamic processes from plasma generation to post-discharge evolution are recorded in detail by a high-speed camera. The visualized images reveal a transition from a laminar to a turbulent region in the flow field outside the tube following discharge excitation. The turning point (turbulent vortex) propagates at a speed of m s-1. The results show that a higher driving voltage leads to an earlier onset of the turbulent vortex and further shortens the laminar zone length, with a maximum reduction of 36%. The turbulent vortex dynamics gradually diminish as the frequency increases, resulting in a maximum 30% reduction in the laminar zone length after the cumulative effect of several cycles. Also, the impact of the pulse width parameter on the flow field is minimal. By observing the changes in the distribution of gas temperature under different discharge parameters, it is concluded that the thermal effect is the main factor influencing the kinetic process of the flow field.

Electrical explosion is a physical process driven by electric current that comes with a conductor to be heated up, undergo phase transitions in form of explosion. It can provide extreme conditions of instantaneous high temperature (>10000 K) and pressure (GPa) in a very short period (<20 μs), accompanied by intense shock waves and light radiation. These characteristics make it a unique but effective methodology for designing and synthesizing composite materials. In this work, polyethylene (PE) was introduced into the electrical explosion process. Therein, a 20-kA current pulse was applied to drive electrical explosion, resulting in a special composites with metal nanoparticles (NPs) adhering to thin PE sheets. The morphology of the material mainly shows small sized metal nanoparticles attached to the large sized polymer surface. A small amount of core-shell structured composites were also observed in the SEM images. Statistical analysis revealed that the shock wave produced in free space during the explosion propagated at a speed of 775 m/s, which enhanced the mixing of different components in the explosion products. This method enabled the rapid modification of polyethylene materials, leading to the preparation of polymer materials attaching with copper and aluminum nanoparticles. Compared with different kinds of raw material, copper foil and copper wire, the former one forms a tighter structure of nanoparticles, and a more uniform distribution. Some of the nanoparticles are even able to be embedded into carbon material. These composites are expected to exhibit diverse properties, offering potential for advanced applications.

Falls are one of the most serious health risks faced by older adults worldwide, and they can have a significant impact on their physical and mental well-being as well as their quality of life. Detecting falls promptly and accurately and providing assistance can effectively reduce the harm caused by falls to older adults. This paper proposed a noncontact fall detection method based on the human electrostatic field and a VMD-ECANet framework. An electrostatic measurement system was used to measure the electrostatic signals of four types of falling postures and five types of daily actions. The signals were randomly divided in proportion and by individuals to construct a training set and test set. A fall detection model based on the VMD-ECA network was proposed that decomposes electrostatic signals into modal component signals using the variational mode decomposition (VMD) technique. These signals were then fed into a multichannel convolutional neural network for feature extraction. Information fusion was achieved through the efficient channel attention network (ECANet) module. Finally, the extracted features were input into a classifier to obtain the output results. The constructed model achieved an accuracy of 96.44%. The proposed fall detection solution has several advantages, including being noncontact, cost-effective, and privacy friendly. It is suitable for detecting indoor falls by older individuals living alone and helps to reduce the harm caused by falls.

Gait stability is an important indicator of human health and physical ability, and it is of great significance for early detection, diagnosis, and rehabilitation of diseases. This article proposes the first comprehensive and in-depth method for quantitatively evaluating gait stability using electrostatic gait signals (EGSs). A quantitative evaluation of gait stability was conducted on the EGSs of ten healthy subjects (HSs) and ten hemiplegic patients (HPs) from three perspectives: variability of gait phase temporal parameters, nonlinear local dynamic stability, and energy frequency band distribution differences. The coefficient of variation [CV( x )] reflects the degree of variation of each temporal parameter. Local dynamic stability is characterized by using the short-term largest Lyapunov exponent ( lambda & lowast;S ) to reflect the sensitivity to local perturbations and to characterize gait stability. Power spectral entropy (PSE) is used to quantify the complexity and instability of the signal in the frequency domain to characterize gait stability. The results showed that the CV( x ), lambda(& lowast;)(S) , and PSE were all significantly greater in HPs than in HSs. The Mann-Whitney test was used to perform significance testing on each indicator between the HS and HP groups. The results showed that, except for the variability of the affected side support phase [CV( T-LHI )], the variability of the other 13 gait temporal parameters, short-term largest Lyapunov exponent ( lambda(& lowast;)(S) ), and PSE differed significantly between the groups ( p<0.05 ). This research explores a feasible technical approach to using EGSs for gait analysis and quantitatively assessing the gait stability of subjects.

The laboratory lightning test is essential for assessing the effectiveness of lightning strike protection (LSP). Particularly, direct lightning strike damage can be performed with pulsed current injection into the specimen. This paper focuses on the dynamic process of arc plasma and shock wave behaviour in the vicinity of the 'strike' point. A rod-plate discharge load is built for testing aluminium and coated plate under 40-kA-level pulsed current. The visualisation of the luminous discharge plasma and its flow field via high-speed photography (from different angles) is meticulously designed and implemented, synchronised with electro-physical diagnostics. The results indicate some new mechanisms for lightning strike damage, apart from the impulse heat loading from the thermal arc. The transient current injection through the arc root concentrates on a thin skin layer (skin-depth effect), with the radial-attenuated current density, driving asynchronously electrical explosions on the plate surface. The inhomogeneous Joule heating of the plate leads to outwardly propagating phase transition and shock wave along the conductive surface. In addition, the electro-thermal instability is observed and regarded as the seed of irregular erosion region. Spectroscopic information reveals two different plasma states of main discharge arc channel and adjacent surface electrical explosion. The correspondence of the physical mechanism of electrical explosion and optical radiation is established. Microscopic images for different regions depict erosion characteristics and summarise influencing factors, further confirming the mechanism above. The research clarifies the role of skin-depth effect in transaction arc erosion for electrode, complements the electrical explosion theory with unevenly distributed current and helps optimise strategies of LSP.

Accurate modeling and estimation of the internal temperature distribution is of great significance to the thermal management of lithium-ion batteries (LIBs). Existing control-oriented models generally assume a uniform temperature distribution along the axial direction of LIB. The ignorance of thermal inhomogeneity however challenges the refined thermal monitoring of LIB. To remedy this deficiency, this paper proposes for the first time a novel distributed thermal model for LIB, by hybridizing the thermal transfer law and the artificial intelligence approach. Relying on the spatial temperatures of LIB obtained by a distributed sensing technique, a lumped-parameter thermal network model is developed to capture the general thermal behavior of LIB. In a cascaded manner, the long short-term memory (LSTM) neural network is proposed to compensate for the thermal inhomogeneities that cannot be explained. The proposed cascaded distributed thermal (CDT) model further proves to be compatible with commonly-used observers for online internal temperature distribution estimation. Experimental results suggest that the proposed distributed model and the associated estimation framework can give space-resolved inner temperature estimation with remarkably-improved accuracy compared with the existing methods.

The combustion of the engine in the air vehicle causes the presence of charged particles in the jet stream, and the electric field displayed varies with engine type and fuel characteristics. In order to show the magnitude and distribution of charged particles in combustion products during scramjet operation, we constructed microphysical model and fluid calculation model based on the physical characteristics of supersonic combustion to simulate the variation of charged particles concentration in the scramjet combustion chamber and the charge density distribution outside the combustion chamber. The obtained results show that the charged particles in combustion products are mainly composed of ions, electrons, ion clusters, and charged soot particles. The electron concentration can be almost negligible at the exit of the combustion chamber. The other charged particles in the combustion products are ejected into the atmosphere with the jet. The charge density distribution of the jet has a certain symmetry in a short time due to the influence of the flow field. It is found that the type of fuel and the conductivity of the surface materials in the combustion chamber affect the electrified properties of the combustion products to some extent. This study has a reference value for further analysis of the detectable electric field generated during scramjet operation.

High-voltage pulsed discharges come with strong transient electromagnetic field due to the fast release of electric energy. Electrical explosion, as a special kind of pulsed discharge, exhibits more interesting electro-physical features than ordinary gas breakdown manner. In this study, we measured the electromagnetic field in the vicinity of an exploding Cu wire load. Meanwhile, the discharge waveforms and high-speed images were captured synchronously. The results revealed that there existed several electromagnetic radiation bursts within a single shot of wire explosion. Further analysis ascertained those radiations were closely related to the current variation through the wire load. In the frequency domain, the spectrum appeared wideband feature, and the majority of the energy is within 200 MHz. In addition, changing the discharge parameters can significantly alter the strength and frequency characteristics of the electromagnetic field and wave.

Accurate assessment of mobility is of great significance for disease diagnosis and rehabilitation guidance. In response to the needs of hemiplegic patients (HPs) for accurate quantitative assessment of mobility during disease diagnosis and rehabilitation, this article proposes a gait analysis method based on the fusion of bimodal gait signals from human electrostatic field and Kinect, which can objectively and quantitatively assess the gait abnormalities of HPs. Kinematic data and human electrostatic gait signals were recorded simultaneously during the walking process of the subjects, and ten quantitative indexes of motion ability and symmetry of hip, knee, and ankle joint, muscle force control ability, gait symmetry, gait balance, and gait stability were extracted. The gait index of HPs was quantitatively assessed by an improved principal component analysis method, which was used to quantitatively assess the lower limb motor function of HPs. The results showed that the hemiplegic gait index was effective in differentiating HPs with different Brunnstrom stages and showed a significant negative correlation with the Fugl-Meyer lower extremity motor function scale scores (P < 0.05), with an absolute value of the correlation coefficient as high as 0.96. This article suggests that the hemiplegic gait index is a reliable mobility assessment tool to better support traditional clinical decision-making and improve the efficiency of rehabilitation therapy.

Gait analysis is an important means for diagnosing related diseases, guiding rehabilitation, and assessing mobility. Compared with existing methods, the non-contact electrostatic induction detection method for obtaining gait signals has the advantages of being non-wearable, low-cost, and capable of directly obtaining full-cycle gait signals for a long time. This paper proposes a theory and method of non-contact electrostatic gait detection based on the human body's electrostatic field. The change law of the equivalent capacitance of the human foot to the ground was analyzed and the kinematic equations of the human foot during movement was established. Based on this, a non-contact electrostatic gait signal detection model based on the human body's electrostatic field was established. Both the simulation curve of the theoretical model and the measured electrostatic gait signal can reflect the gait information of the foot movement, especially initial contact (IC), toe-off (TO), and swing phase, and have high consistency. This research provides a new theoretical basis and feasible technical approach for gait measurement and analysis.

The parametric relationships between underwater shock waves (SWs) in far-field regime and electrically exploded wire under different charging voltages of a generator are investigated. Contributions of the vaporization and current restrike to the resulting SWs have been examined by means of electro-physical diagnostics, free-field pressure probe, and high-speed photography. In the experiment, a 6-mu F pulse capacitor is adopted to provide a microsecond timescale pulsed current, exploding a 90/185-mu m-diameter, 2-cm-long copper wire with the charging voltage ranging from 7.1 kV (stored energy similar to 150 J) to 18.3 kV (similar to 1000 J). Experimental results indicate that as the increase of the charging voltage, the relationship between electro-physical and shock wave parameters shows a rather complex situation. When the charging voltage ranging from 7.1 kV (similar to 150 J) to 11.6 kV (similar to 400 J), the peak pressure of SWs (300 mm away from the explosion source) increases almost linearly from 1.16 +/- 0.03 to 2.24 +/- 0.05 MPa (90-mu m wire), and 1.67 +/- 0.17 to 2.87 +/- 0.12 MPa (185-mu m wire). Nevertheless, at a higher charging voltage between 11.6 kV (400 J) to 14.1 kV (600 J), the peak pressure stabilizes in a strange "plateau". Until the residual energy after the explosion is sufficiently large (>600 J in this study) to induce a strong current restrike, the development of the plasma channel could further enhance the expansion of explosion products, as well as the intensity of measured SWs. In addition, high-speed photography has been applied for those explosions, providing the information of plasma channel expansion and initial SWs propagation.

Gait analysis is a technique facilitating disease diagnosis, rehabilitation, and mobility assessment. The gait detection approach based on the human electric field is noncontact and portable while providing real-time gait data. This article presents a noncontact gait detection method based on a full-cycle gait characteristic detection model. Based on electrodynamics theory, a complex variable function method evaluating static fields under complex boundary conditions was used, an equivalent plantar capacitance calculation model was proposed, and a full-cycle gait characteristic detection model was established. The simulation results showed that the calculation model greatly improved the plantar capacitance accuracy, and the rationality and validity of the model were qualitatively verified through human electrostatic potential and gait data, so the detection model reflected the time-domain signal and detailed characteristics of the full-cycle gait. VICON was used to acquire the simulated abnormal gait and to verify the correctness of the detection model and system. The clinical gaits of patients with Parkinson’s and hemiplegia were collected to verify the effectiveness of the method to reflect full-cycle time-domain signals and extract abnormal gait information. This study provides a theoretical basis and feasible gait analysis method to obtain full-cycle information about natural gait.