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Bearing remaining useful life (RUL) prediction has always been a central topic in the industry field, which is aimed to optimize system safety and sustainability. The validity of the prediction model and the accuracy of the prediction results are affected by mid-term singularities and terminal mutations, under the time-domain bearing vibration information. In this paper, a network structure-Cascaded dilated convolution vision informer (CDC-Vii) is put forward to precisely forecast the RUL of bearings, which uses the time-frequency fault features as input. CDC-Vii breaks the limitation of the Original Informer which is only sensitive to time series information. An adaptive fault frequency band selection (AFFBS) algorithm is proposed, which can reduce training time while utilizing rich time-frequency information. Based on the Informer architecture, the attention mechanism is improved to form vision subsampling ProbSparse self-attention(VSPS). VSPS can precisely assign spatial attention weights and reduce computational complexity. At the same time, a truncated relative position encoding (TRPE) technique is proposed to strengthen the position dependence between attention information. Moreover, Cascaded dilated convolution (CDC) enhances the image contrast of faulty frequency bands while enlarging the use of receptive field. Experiments on extensively utilized two bearing datasets reveal that CDC-Vii surpasses the advanced RUL prediction models.

The development of high efficiency oxygen evolution electrocatalyst is of great significance for water splitting reaction. Herein, an efficient cone-structured NiFe-LDH/Nicone/Ti catalyst is fabricated by electrodeposition method towards enhanced oxygen evolution reaction (OER). The featured tip curvature of nanocone structure can accelerate the reaction kinetics of OER by offering a field-enhanced aggregation of local hydroxide ion reactant on the catalyst surface, and thus improves the performance of the NiFe catalyst. Accordingly, NiFe-LDH/Nicone/Ti requires only a low overpotential of 292 mV to achieve 50 mA cm−2, and with high stability under continuous high-current operations. In addition, the alkali-electrolyzer using NiFe-LDH/Nicone/Ti electrode exhibits good performance with a voltage of 1.73 V at 50 mA cm−2 and displays excellent stability in long-term stability test. This cone-structured catalyst design with field-enhanced local hydroxide ion aggregation effect provides a promising method for the development of highly active OER electrocatalysts.

The auxiliary heating of electrons and ions in linear plasma devices (LPDs) is necessary to achieve the boundary plasma relevant environment of tokamaks, to investigate the boundary physics and plasma—material interactions. In this work, the simulation of ion cyclotron resonance heating (ICRH) in the LPD multiple plasma simulation linear device (MPS-LD) is carried out by using a 3D particle-in-cell method, and the wave—ion interaction mechanism based on a ‘beach-heating’ technique in the ion heating region is investigated. A left-handed, circularly polarized wave along the magnetic field lines is used to represent the electromagnetic wave in the model, after the analysis of the cold plasma dispersion relation. The mechanism of ion heating by collisionless damping absorption is demonstrated and explained by using the plasma current as the plasma response. The dependencies of the heating efficiency on the plasma density, magnetic field strength and magnetic field configuration are studied. The correlation between plasma density and magnetic field strength, which satisfies the heating efficiency, is found and it is in perfect agreement with the theoretical derivation. Finally, by using the designed parameters of MPS-LD provided by SOLPS-ITER, the prediction of ICRH is performed. The simulation result shows that the ion temperature can be heated higher than 40 eV and it satisfies the requirement for scrape-off layer/divertor simulation experimentally in MPS-LD.

Stochastic resonance (SR) can enhance signals by using noise. This has attracted more attention in the field of weak signal detection. In practical applications, owing to the non-adjustability of noisy signals, SR is required to adjust the system parameters adaptively to satisfy the conditions of the SR phenomenon. In this paper, an adaptive progressive learning SR method is proposed to improve the detection ability for weak signal, and the SR phenomenon is quantitatively defined. A theoretical learning framework is established with an improved reinforcement learning model by mapping the nonlinear system parameter space to a progressive learning set. By selecting a proper learning layer within a determined constraint range, the matching system parameters can be quickly and accurately searched to generate a desired optimal output. Numerical simulation results show that the signal energy and the output signal-to-noise ratio (SNR) can be enhanced significantly, which reflects an excellent weak signal detection performance especially for low SNR conditions. Finally, a diagnosis of the outer race fault signals of a rolling bearing confirms that the proposed method can effectively detect fault characteristics.

Collisional-merging is a way to form high-performance field-reversed configuration (FRC) plasma. An experiment device named HUST-FRC (HFRC) is under construction in Huazhong University of Science and Technology, which will be used to investigate the FRC formation through collisionalmerging. In this research, a magnetohydrodynamics simulation software called USim is used to study the effect of the initial density of plasma, the amplitude of the bias magnetic field, the configuration of the bias field, the rise time of the main field and the magnetic field ripple on the plasma parameters to facilitate the design and operation of HFRC. Preliminary simulation results show that cusp configuration, lower ripple, higher initial density, an initial bias field of −0.15 T or −0.2 T, and a rise time of 4 μs are conducive to the formation of high-performance FRC plasma in the HFRC device.

At present, the effective integration of information technology and feedback control law represented by computer simulation training can effectively collect and manage the sports information of athletes, so as to improve the scientificity and rationality of athletes’ training, so it has important research value. Based on this, this paper first analyzes the theory and method of track and field teaching and training, then studies the application of feedback control law in track and field teaching, and finally analyzes the application of feedback control law in track and field computer simulation training.

Global linear gyrokinetic simulations using realistic DIII-D tokamak geometry and plasma profiles find co-existence of unstable reversed shear Alfvén eigenmodes (RSAE) with low toroidal mode number n and electromagnetic ion temperature gradient (ITG) instabilities with higher toroidal mode number n. For intermediate n = [10, 12], RSAE and ITG co-exist and overlap weakly in the radial domain with similar growth rates but different real frequencies. Both RSAE and ITG growth rates decrease less than 5% when compressible magnetic perturbations are neglected in the simulations. The ITG growth rates increase less than 7% when fast ions are not included in the simulations. Finally, the effects of trapped electrons on the RSAE are negligible.

In order to improve the marine corrosion resistance of the copper alloy, the method of synergistic modification was introduced to prepare the in situ coating on the surface of HSn62-1 by laser shock melt injection of fine-CeO2 particles. The micrograph and microstructure of the Hsn62-1, in situ coating, and the laser-treated sample were investigated in contrast. Besides, the electrochemical corrosion resistance of the three specimens in 3.5% NaCl solution was studied. The results demonstrated that the in situ coating had good compactness and no apparent defects. The upper part of the in-suit coating was mainly cellular solidification microstructure, while the microstructure in the middle and lower part was coarse dendrite. Compared with Hsn62-1 copper alloy, the corrosion resistance of the laser-treated sample and the in-suit coating were improved, which proved that the synergistic modification of laser and rare earth could improve the corrosion resistance of the copper alloy. The analysis indicated that the rare earth elements in the in-suit coating would undergo hydrolysis reaction to form the dense rare-earth hydroxide in an ‘island growth’ way, which effectively prevented the invasion of corrosion ions.

In severe cold environment, the surface of dry type air-core reactor would easily be cracked, once natural contamination accumulated on the cracks, surface flashover would have more possibility to happen, leading to more serious reactor faults. The most commonly used methods to avoid reactor surface discharge includes RTV coating and surface decontamination using water-based cleaning agent, yet the effects of these methods, as well as possible impact on reactor performance have not been fully studied. In this paper, RTV coating and decontamination tests were carried out to evaluate the effect of the methods, also the impact of these two methods on reactor electrical performance were analyzed. The research result showed that: (1)Water-based cleaning agent was effective in removing contamination on insulation paint surface, but less effective in removing contamination on RTV coated surface; However, the water-based cleaning agent would cause damping between the winding strands, and damping recovery degree was not easy to control. Therefore, water-based cleaning agent was not suitable to solve surface flashover problem of dry type air-core reactors. (2) The overall coating for reactor surface and air duct could be realized by special spraying equipment. The adhesion test showed that RTV was of good covering and adhesion performance, and had little impact on reactor temperature rise, indicating that RTV could be an effective measure to improve operation quality of dry type air-core reactor in extreme cold environment.

PSOD process has serious hysteresis phenomenon and belongs to the large hysteresis system. On the basis of analyzing the working mechanism of the system, the PID control, Smith predictive control and fuzzy control are combined to control the system. Simulation results show that the proposed method has better dynamic performance than the traditional PID control method, regardless of the given input or interference. The conclusion is valuable for the safe operation and control of time-delay systems.

In the process of operation command, the commanders often face a mass of battlefield information information, which mixed with many useless or even false information, This will seriously affect the commander’s timely decision-making, and would not meet the requirements of "agile command" for future operations, By constructing military knowledge model, the fault problem of command information system can be eliminated,and finally, the commander will change from "information" to "knowledge".This paper introduces the main contents and related technologies of military knowledge model, and summarizes the development and challenges of military knowledge model.

In this paper, the experimental data of five different working states of the gearbox during the normal operation and the failure of the gearbox are taken as the research object, the python-based data analysis tools Numpy and Pandas are used to establish a fault detection model, by collecting time-domain and frequency-domain data of several faults such as fracture, crack and wear of transmission gear, and analyzing the characteristic parameters of the data, the classification of transmission faults is realized, thus laying a foundation for the application of big data tools in fault diagnosis and analysis.

The combination of plasma and catalyst can better promote the gas reaction for plasma catalysis. We used a two-dimensional particle-in-cell/Monte Carlo collision model to study the relationship between plasma behavior and dielectric beads with five different packing beads methods in a packed-bed dielectric barrier discharge in nitrogen gas at atmospheric pressure. The electron density, electric field, excitation rate, and ionization rate are calculated with different packing beads methods. As a result, either a change of the bead size or removing one bead can induce distinct features for plasma formation and streamer propagation. The electric field is enhanced near the beads and plates, resulting in a large tangential component to the dielectric surface, giving rise to surface ionization waves (SIWs). The plasma streamer is generated between bead 1 and 2, then propagates to bead 4 and develops itself by surface SIWs along the bead 4 surface, yielding highest and uniform plasma density there with five packing beads. A positive streamer is generated for removing bead 2, and a volume discharge is developed for removing bead 4, asymmetric SIWs are induced with a smaller size of bead 4 while it becomes almost symmetric with a larger size of bead 4 for removing bead 5. The uniform and maximum ionization rate take place on the bead 4 surface, indicating the importance of bead 4 for packing. Moreover, the SIWs and positive streamers give rise to the highest plasma concentration due to the maximum ionization rate on the surfaces of the beads.

In order to accurately identify cattle, help insurance companies to deremine claim of Cattle Insurance, or realize inteligent breeding. We need a cattle face recognition technology. Due to the difficulty in data collection of cattle face and the small amount of data, it is difficult to apply deep learning method to cattle face recognition. So there is a method combined with tarnsfer learning effectively trains the model,or initializes the network weights by parametric transfer. This paper proposed using VGGFace dataset pre-training network to solve the problem of small sample face recognition. The VGG-16 deep convolutional neural network model was used to extract the cattle’s face features. The model parameters obtained by training the VGGFace face dataset were used to initialize the network weights, and then the network was trained on the cattle face dataset. The experimental results show that the method can obtain 93% recognition accuracy under small sample data.

In order to face emergency situation of the rail vehicle air conditioning system, a cool storage device was designed. The device was made up of phase change paraffin and heat exchanger. For the purpose of optimum system design, the mathematic model of phase change and heat transfer in process of cool discharging was established, numerical simulation was finished. Discharging rate of cool and cooling capacity of the device was analyzed. According to the calculation results, the wind speed and air temperature had the greatest influence on the cooling effect, while the thermal conductivity had little effect on it.

Manipulating the self-assembly of transition metal telluride nanocrystals (NCs) creates opportunities for exploring new properties and device applications. Iron ditelluride (FeTe2) has recently emerged as a new class of magnetic semiconductor with three-dimensional (3D) magnetic ordering and narrow band gap structure, yet the self-assembly of FeTe2 NCs has not been achieved. Herein, the tree-like FeTe2 nanoarchitectures with orthorhombic crystal structure have been successfully synthesized by hot-injection solvent thermal approach using phosphine-free Te precursor. The morphology, size, and crystal structure have been investigated using transmission electron microscopy (TEM), high-resolution TEM (HRTEM), and powder x-ray diffraction (XRD). We study the formation process of tree-like FeTe2 NCs according to trace the change of the sample morphology with the reaction time. It was found that the FeTe2 nanoparticles show oriented aggregation and self-assembly behavior with the increase of reaction time, which is attributed to size-dependent magnetism properties of the samples. The magnetic interaction is thought to be the driving force of nanoparticle self-organization.

In this study, hybrid silicon carbide fabrics (SiC)/epoxy composites were fabricated and analyzed. The hybrid SiC fabrics used as reinforcement in the composite was obtained by weaving two types of SiC fibers from two different suppliers: KD-1SiC fibers and SLF-SiC fibers. We have woven these two types of fibers in various proportions. Because the electrical conductivity of KD-1 SiC fiber is much higher than that of SLF-SiC fiber, we have concentrated only on the volume fraction of KD-1SiC fiber and its major influence on the electromagnetic properties of hybrid SiC fiber/epoxy composites. The results indicated that the complex permittivity of the composites increased with increasing the volume fraction of KD-1SiC fiber due to the high interfacial polarization and dielectric loss ability of KD-1SiC fiber. Though the complex permittivity of the composites can be adjusted, the absorbing properties of hybrid SiC fabrics were not greatly enhanced due to the poor impedance matching characteristics. This method provided a way to adjust the complex permittivity of radar absorbing structures.

In this study, the nano-structure MoS2 with the diameter of 40?60 nm was synthesized through a simple hydrothermal method and the carbonyl iron@SiO2 particles were prepared by the Stober method. The electromagnetic properties (?', ?'', ?', ?'') of MoS2/carbonyl iron@SiO2 were measured by the vector network analyzer in the frequency range of 8.2?12.4 GHz for three samples with different MoS2 content. The results shown that the values of complex permittivity and complex permeability can be tailored by the MoS2 content. Compared with carbonyl iron@SiO2 absorbent, the MoS2/carbonyl iron@SiO2 exhibited better absorbing performance at higher frequency range. When the MoS2 content was 15 wt%, the minimum reflection loss value can reach ?28 dB at 12.4 GHz when the thickness was 1.6 mm.

Nowadays, the service robots have been applied in many public circumstances; however, most of them still don't have the function of speech interaction, especially the function of speech-emotion interaction feedback. To make the robot more humanoid, Arduino microcontroller was used in this study for the speech recognition module and servo motor control module to achieve the functions of the robot's speech interaction and emotion feedback. In addition, W5100 was adopted for network connection to achieve information transmission via Internet, providing broad application prospects for the robot in the area of Internet of Things (IoT).

Geometrically symmetric and electrically asymmetric discharges operating at 13.56 MHz and 27.12 MHz with variable phase angle between the harmonics are simulated by a one-dimensional implicit particle-in-cell/Monte Carlo collision model in argon at a pressure of 30 mTorr. The amplitude of each of the harmonics is chosen to be 150 V. The magnetic fields, with strengths of 10 G and 100 G, are parallel to the electrodes and homogeneous throughout the entire electrode gap in a direction perpendicular to the electrodes. It is found that, with a weaker magnetic field at 10 G, the plasma density is nearly doubled and the self-bias is almost unaffected. However, with a stronger magnetic field at 100 G, the plasma density is significantly increased and nearly independent of the phase angle, but at the cost of decreasing the self-bias, which results in a smaller adjustable range of ion bombardment energy. In general, we have demonstrated that an external magnetic field will expand the operational parameter spaces and thus may promote some related applications in coupled plasma sources with electrical asymmetry effects.

Recent findings about ultrahigh thermoelectric performances in SnSe single crystals have stimulated research on this binary semiconductor material. Furthermore, single-layer SnSe is an interesting analogue of phosphorene, with potential applications in two-dimensional (2D) nanoelectronics. Although significant advances in the synthesis of SnSe nanocrystals have been made, fabrication of well-defined large-sized single-layer SnSe flakes in a facile way still remains a challenge. The growth of single-layer rectangular SnSe flakes with a thickness of ~6.8 A and lateral dimensions of about 30 µm × 50 µm is demonstrated by a two-step synthesis method, where bulk rectangular SnSe flakes were synthesized first by a vapor transport deposition method followed by a nitrogen etching technique to fabricate single-layer rectangular SnSe flakes in an atmospheric pressure system. The as-obtained rectangular SnSe flakes exhibited a pure crystalline phase oriented along the a-axis direction. Field-effect transistor devices fabricated on individual single-layer rectangular SnSe flakes using gold electrodes exhibited p-doped ambipolar behavior and a hole mobility of about 0.16 cm2 V−1 s−1. This two-step fabrication method can be helpful for growing other similar 2D large-sized single-layer materials.

Enhanced formation of aerobic granulation was investigated by adding yellow earth as a nucleating agent in a sequencing batch reactor with a constant setting time of 10 min. As a result, granules with an average diameter over 1 mm were obtained on the 4th day. The mature granules behaved better than the seed sludge in the water content, specific gravity, sludge volume index, settling velocity, and specific oxygen uptake rate. The yellow earth stimulated the secretion of extracellular polymeric substances, especially proteins. Both chemical oxygen demand and ammonia nitrogen had a removal rate over 90%, and more than 80% of the total inorganic nitrogen was removed even under aeration conditions due to simultaneous denitrification. The enhancement effects of the yellow earth might be based on the unique physicochemical characteristics and short settling time. A settling time of 10 min or more turned out not to be a prerequisite for a rapid granulation process.

The plasma behavior in a parallel-plate dielectric barrier discharge (DBD) is simulated by a two-dimensional particle-in-cell/Monte Carlo collision model, comparing for the first time an unpacked (empty) DBD with a packed bed DBD, i.e., a DBD filled with dielectric spheres in the gas gap. The calculations are performed in air, at atmospheric pressure. The discharge is powered by a pulse with a voltage amplitude of −20 kV. When comparing the packed and unpacked DBD reactors with the same dielectric barriers, it is clear that the presence of the dielectric packing leads to a transition in discharge behavior from a combination of negative streamers and unlimited surface streamers on the bottom dielectric surface to a combination of predominant positive streamers and limited surface discharges on the dielectric surfaces of the beads and plates. Furthermore, in the packed bed DBD, the electric field is locally enhanced inside the dielectric material, near the contact points between the beads and the plates, and therefore also in the plasma between the packing beads and between a bead and the dielectric wall, leading to values of V m−1, which is much higher than the electric field in the empty DBD reactor, i.e., in the order of V m−1, thus resulting in stronger and faster development of the plasma, and also in a higher electron density. The locally enhanced electric field and the electron density in the case of a packed bed DBD are also examined and discussed for three different dielectric constants, i.e., (ZrO2), (Al2O3) and (SiO2). The enhanced electric field is stronger and the electron density is higher for a larger dielectric constant, because the dielectric material is more effectively polarized. These simulations are very important, because of the increasing interest in packed bed DBDs for environmental applications.

We benchmark and analyze the error of energy conservation (EC) scheme in particle-in-cell/Monte Carlo (PIC/MC) algorithms by simulating the radio frequency discharge. The plasma heating behaviors and electron distributing functions obtained by one-dimensional (1D) simulation are analyzed. Both explicit and implicit algorithms are checked. The results showed that the EC scheme can eliminated the self-heating with wide grid spacing in both cases with a small reduction of the accuracies. In typical parameters, the EC implicit scheme has higher precision than EC explicit scheme. Some "numerical cooling" behaviors are observed and analyzed. Some other errors are also analyzed. The analysis showed that the EC implicit scheme can be used to qualitative estimation of some discharge problems with much less computational resource cost without much loss of accuracies.