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The coupling between the positive and negative poles of the bipolar DC microgrid will influence the voltage control which makes it difficult to compute the parameters of the control loop independently. The unbalanced voltage in the bipolar DC microgrid is a special power quality problem. The suppression of unbalanced voltage is a significant work in operation planning. In this paper, the expressions of voltage unbalance coefficient and distribution line current is deduced to investigate the influence of unbalanced loads on voltage deviation, voltage unbalance coefficient, and current distribution accuracy. On this basis, the common-mode and differential-mode consensus control of the bipolar DC microgrid is proposed to improve the dynamic performance of the control system and reduce the voltage deviation and voltage unbalance coefficient. In addition, the small-signal stability is analyzed in this paper. To verify the effectiveness of the proposed modulus control method in the bipolar DC microgrid, a MATLAB/Simulink simulation platform, and a low-voltage experimental platform are established. The proposed modulus control is better than the droop control in regulating unbalanced voltage. In addition, it is still effective under the influence of load change. Moreover, the unbalanced voltage can be controlled when addition PV and BEMS are added in the bipolar DC microgrid.

A visual system is a key tool for automatic fruit harvesting. It faces the challenges of varied occlusion and illumination in the field, resulting in difficulties in fruit recognition and picking. At present, there are many studies that lack a comprehensive analysis of the impact of the environment on harvesting. This study proposes an object–environment fusion visual system. It comprises modules for object perception, environment perception, and picking pose estimation. The object perception module aims to identify and locate pears. The environment perception module is deployed to analyze the three-dimensional (3D) information of objects and obstacles. Finally, the picking pose estimation module fuses the information of the objects and environment to calculate the collision-free picking position and orientation. Additionally, specific implementations are employed for each module. It compares three networks to identify pears for object perception. Voxel-based representation is used to simplify point clouds for environmental perception. A sampler and evaluator are applied for picking pose estimation. The S1 and S2 datasets were acquired in a laboratory pear tree model and the orchard of Zhejiang Academy of Agricultural Sciences, respectively, to evaluate the proposed method. In the S2 dataset, the success rate for picking pose estimation reached 87.11% within the distance range of 30∼50 cm. All of the results demonstrate that the proposed method can be applied to visual perception for automatic pear harvesting.

MAX phase solid solutions obtained by alloying at M-, A- and X-sites have attracted much attention recently to adjust the lattices and control the properties of MAX phases. In this work, a series of porous Ti3(Al,Si)C2 solid solutions were fabricated by pressureless sintering with Ti/Al/Si/TiC powder mixtures. Pore structures and effects of Si content were systematically characterized. The Si substitution affected the pore structure of porous Ti3(Al,Si)C2 following a V-shaped law: when xSi≤0.4, the porosity decreased together with the reduced pore size, narrow distribution and increased tortuosity factor; when xSi>0.4, the porosity and pore size increased together with the decreased tortuosity factor. Considering the specific application as capillary wick materials, the capillary performance, compressive strength and thermal conductivity of porous Ti3(Al,Si)C2 solid solution were further measured. The results showed that the larger porosity improved the capillary performance, but decreased the compressive strength and thermal conductivity. Compared with porous Ti3AlC2 of similar porosity, porous Ti3Al0.4Si0.6C2 had smaller pore size with more concentrated distribution, but better overall performances (the much better capillary performance, higher compressive strength and lower thermal conductivity). It was demonstrated that the adapt Si substitution achieved the overall promotions of porous Ti3AlC2, and porous Ti3Al0.4Si0.6C2 solid solution could act as the novel wick materials and show broad prospects in loop heat pipes (LHPs).

Loop heat pipes (LHPs) have consistently garnered attention for effectively managing thermal conditions in critical electronic components of spacecraft and satellites. Particularly intriguing are LHPs equipped with bi-porous capillary wicks, demonstrating commendable flow and thermal dissipation capabilities. Despite its significance for evaluating the phase-transition heat transfer in porous structures, the effective thermal conductivity (ETC) has not been understood mechanistically. This study aims to establish an efficient procedure for predicting ETC in bi-porous wicks through a comparative analysis of analytical and numerical methods. The analytical ETC expression was formulated using thermal resistance network and neck formation theory. Meanwhile, the numerical model utilized the Finite volume method (FVM) combined with a 3D porous structure created by Diffusion-Limited Aggregation (DLA) algorithm. The investigation revealed a congruence between two methods and the measured ETCs of interstitial-pore samples containing fine nickel powders. However, undesirable results were shown for coarse samples due to the irregular particle shapes. In samples with formation pores, the numerical model excels in characterizing the spatial distribution and scale of pores, albeit at the expense of time consumption and model complexity compared to the analytical one. Both methods prove valuable for ETC modeling of sintered bi-porous structures according to desired applications.

The unbalanced loads and distributed generations (DGs) will lead to an unbalanced current in the neutral line and further result in a voltage imbalance which will increase circuit power consumption and affect the stable operation of the bipolar DC microgrid. The application of a voltage balancer (VB) can address the issue of unbalanced voltage and current. In this paper, the proposed coordinated control strategy can realize VB to provide a reference voltage to voltage source converter (VSC), battery energy management system (BEMS), and photovoltaic (PV) power generation. The essence of the proposed coordinated control strategy is to adaptively adjust the voltage droop coefficient, which can realize the suppression of unbalanced voltage, power sharing, and regulation of battery state of charge (SOC). In this research, the coordinated control structure of VB and the control scheme of BEMS are investigated. In addition, the small-signal model of the bipolar DC microgrid is also presented to show the system involved is stable. Subsequently, the effectiveness of the proposed coordinated control strategies is verified in MATLAB/Simulink software.

Abstract The difficulty of anomaly detection lies in balancing the impact of noise on the network (noise suppression) and distinguishing the real anomaly from the noise (abnormal exposure). So, a deep anomaly detector Batch Quadratic Programming (BQP) network with Maximum Entropy Constraint is proposed. It imposes quadratic programming constraints on Support Vector Data Description through the BQP output layer to achieve noise suppression. In BQP network processes’ batch data, Maximum Entropy Constraint is used to balance abnormal samples and noise. The experiment compared the shallow method with the currently popular deep method on MNIST and CIFAR‐10 data sets and proved that the BQP network with Maximum Entropy Constraint has excellent performance.

Bi-porous Ti3AlC2 wicks with the controllable pore structure were fabricated with the dissolvable pore former NaCl and cold pressure in this work. The bi-porous structure consisted of fine gap pores (

In high-temperature reverse-bias test of an insulated-gate bipolar transistor module, the problem of self-heating in chip resulting from power loss arises with high frequency. To address this problem, the law of the variation in leakage current with temperature for the reverse-bias state of a device is derived and utilized to establish a temperature calibration curve, with which the online measurement of the insulate-gate bipolar transistor module chip temperature can be implemented directly by real-time monitoring of device leakage current in high-temperature reverse-bias test. The method we proposed solves the problem of large measurement error in chip temperature obtained by traditional thermal resistance calculation method. In addition, real-time chip temperature can be monitored without introducing additional test circuit or HTRB interruption experiment. To demonstrate the effectiveness of the proposed method, the switching small-current temperature measurement method is used to make comparison, and the experiment result indicates that the temperature of the chip in the blocking test can be obtained with high precision by using the leakage current measurement method presented in this work.

The latent variable prior of the variational autoencoder (VAE) often utilizes a standard Gaussian distribution because of the convenience in calculation, but has an underfitting problem. This paper proposes a variational autoencoder with optimizing Gaussian mixture model priors. This method utilizes a Gaussian mixture model to construct prior distribution, and utilizes the Kullback-Leibler (KL) distance between posterior and prior distribution to implement an iterative optimization of the prior distribution based on the data. The greedy algorithm is used to solve the KL distance for defining the approximate variational lower bound solution of the loss function, and for realizing the VAE with optimizing Gaussian mixture model priors. Compared with the standard VAE method, the proposed method obtains state-of-the-art results on MNIST, Omniglot, and Frey Face datasets, which shows that the VAE with optimizing Gaussian mixture model priors can learn a better model.

The flow mechanism within a silicon-based micro heat sink plays a crucial role in two-phase thermal dissipation technology. In this study, the effect of geometrical properties on the flow behavior within a silicon-based array parallel microchannel as the evaporator of a silicon-based micro loop heat pipe (s-mLHP) is experimentally and numerically investigated. Here, three arrayed microchannels with different aspect ratio (AR) parameters (depth of 180 μm and AR of 6, 9, and 15) are specially fabricated. A visual experiment platform is established to observe and measure capillary properties of microchannels characterized by the suction distance. In addition, a validated numerical model (the maximum deviation less than 38.3%) is applied to simulate the flow characteristics of microchannels with different ARs. Numerical solutions show that the microchannel with ARs taken between 3 and 4 achieves the best capillary pumping performance within the studied range (suction distance up to 0.8 mm), which provides a theoretical basis for further exploration of silicon-based microchannel array with the optimal flow and thermal performance.

As a type of micro flat loop heat pipe, s-UTLHP (silicon-based ultra-thin loop heat pipe) is of great significance in the field of micro-scale heat dissipation. To prove the feasibility of s-UTLHP with high heat flux in a narrow space, it is necessary to study its heat transfer mechanism visually. In this paper, a structural design of s-UTLHP was proposed, and then, to realize the working fluid charging and visual experiment, an experimental system including a holding module, heating module, cooling module, data acquisition module, and vacuum chamber was proposed. Deionized water was selected as a working fluid in the experiment. The overall and micro phenomena of s-UTLHP during startup, as well as the evaporation and condensation phenomena of s-UTLHP during stable operation, were observed and analyzed. Finally, the failure phenomenon of s-UTLHP was analyzed, and several solutions were proposed. The observed phenomena and experimental conclusions can provide references for further related experimental research.

Both synthesis and analysis sparse regularisation have been successfully applied to solve various inverse vision problems. The authors find an optimisation model to combine the power of the dual sparse prior models for image restoration. Specifically, for each local patch, adaptive switching on using synthesis or analysis sparse regularisation is performed for better restoration quality. In addition, cluster-specific synthesis and analysis sub-dictionary learning, based on principal component analysis method and sequential minimal eigenvalues algorithm, is incorporated into the joint sparse models to achieve maximum indices gains. The efficient alternating strategy is exploited to solve the optimisation problem. Experimental results highlight the superiority of the proposed approach compared with the state-of-the-art methods, especially in terms of better image structures preservation.

Abstract Sb2S3 has attracted great research interest very recently as a promising absorber material for photoelectric and photovoltaic devices because of its unique optical and electrical properties and single, stable phase. However, the intrinsic high resistivity property of Sb2S3 material is one of the major factors restricting the further improvement of its application. In this work, the C60 modification of Sb2S3 thin films is investigated. The conductivity of Sb2S3 thin films increases from 4.71 × 10−9 S cm−1 for unmodified condition to 2.86 × 10−8 S cm−1 for modified thin films. Thin‐film solar cells in the configuration of glass/(SnO2:F) FTO/TiO2/Sb2S3(C60)/Spiro‐OMeTAD/Au are fabricated, and the conversion efficiency is increased from 1.10% to 1.74%.

Loop heat pipe, carried out by liquid-gas phase transition, has been attracted as an efficient heat management device in high-heat-flux, long-distance and anti-gravity situations. The capillary pressure provided by the porous wick in the evaporator drives circulation for working liquid, affecting the heat exchange efficiency for loop heat pipes directly. In this work, the bi-porous Ti _3 AlC _2 wick was produced by reaction sintering and pore formers dissolution and porosity and pore size were regulated by varying pore formers content and cold pressure. The pore size distribution was characterized by mercury intrusion and effects on capillary performance and thermal conductivity were also analyzed. The porosity and proportion of large pores increased with the increased pore formers content, causing the enhancement of capillary performance and the reduction of thermal conductivity. As the cold pressure increased, pore size distribution concentrated, the proportion of fine pores increased and the porosity fluctuated slightly, increasing the capillary pressure and improving capillary performance and thermal conductivity. Based on experimental results, the parameter of pore size proportion was proposed to modify the Alexander model to predict the thermal conductivity of porous materials accurately, guide the design for pore structure and promote the transfer capacity.

As a phase change evaporator, a microchannel array heat exchanger is of great significance in the field of microscale heat dissipation. The performance of which strongly depends on the flow resistance, capillary force, and other factors. In order to improve the heat dissipation efficiency, it is necessary to perform an in-depth study of the characteristics of microchannel flow using numerical simulation. However, the current simulation model requires high computational cost and long simulation time. To solve this problem, this paper simplifies the numerical simulation of the rectangular parallel array microchannels by building the basic flow model based on the concept of porous media. In addition, we explore the effect of aspect-ratio (AR), hydraulic diameter, inlet velocity, and other parameters of fluid flow behavior inside the microchannels. Meanwhile, a user-defined function (UDF) is formulated to add the capillary force into the model to introduce capillary force into the porous media model. Through the above research, the paper establishes the porous media model for single-phase and gas-liquid two-phase flow, which acts as a simplification of microchannel array simulation without grossly affecting the results obtained. In addition, we designed and manufactured experiments using silicon-based microchannel heat exchangers with different-ratios, and combined with the visualization method to measure the performance of the device and compared them with simulation results. The theoretical model is verified through the suction experiment of array microchannel evaporator capillary core. The simplified model of microchannel array significantly saves the computational cost and time, and provides guidance for the related experimental researches.

Time synchronization is essential for node localization, target tracking, data fusion, and various other Wireless Sensor Network (WSN) applications. To improve the estimation accuracy of continuous clock offset and skew of mobile nodes in WSNs, we propose a novel time synchronization algorithm, the Rao-Blackwellised (RB) particle filter time synchronization algorithm based on the Dirichlet process mixture (DPM) model. In a state-space equation with a linear substructure, state variables are divided into linear and non-linear variables by the RB particle filter algorithm. These two variables can be estimated using Kalman filter and particle filter, respectively, which improves the computational efficiency more so than if only the particle filter was used. In addition, the DPM model is used to describe the distribution of non-deterministic delays and to automatically adjust the number of Gaussian mixture model components based on the observational data. This improves the estimation accuracy of clock offset and skew, which allows achieving the time synchronization. The time synchronization performance of this algorithm is also validated by computer simulations and experimental measurements. The results show that the proposed algorithm has a higher time synchronization precision than traditional time synchronization algorithms.

As one of the most promising micro-machining methods, electrochemical micro-machining is widely used in the field of metal micro-structures. The electrochemical micro-milling on Nickel-base superalloy by using high-speed spiral electrode was studied in detail. Firstly, the electric field and flow field models of micro-electrochemical milling are established and analyzed by the finite element method. Then, the milling profile was predicted and the effect of high-speed rotation of electrodes on electrolyte promotion and secondary electrolysis prevention were analyzed. Secondly, the influence of the main machining parameters, such as rotating speed, electrical parameters, and feed rate on machining precision and efficiency was analyzed experimentally. Finally, by optimizing the machining parameters, a series of micro-graphic structures with a width of about 150 μm were obtained on Nickel-base superalloy 718 by using the spiral electrode with a diameter of 100 μm. The experimental and simulation results show that the high-speed rotation of electrodes can greatly improve the machining efficiency and stability. It was proved that micro-electrochemical milling with the high-speed rotating electrode technique is an effective method for machining micro-metal parts.

Micro electrochemical machining is becoming increasingly important in the microfabrication of metal parts. In this paper, the machining characteristics of micro electrochemical milling with nanosecond pulse were studied. Firstly, a mathematical model for the localization control of micro electrochemical milling with nanosecond pulse was established. Secondly, groups of experiments were conducted on nickel-based superalloy and the effects of parameters such as applied voltage, pulse on time, pulse period, electrolyte concentration and electrode diameter on machining localization and surface roughness were analyzed. Finally, by using the optimized machining parameters, some 2D complex shapes and 3D square cavity structures with good shape precision and good surface quality were successfully obtained. It was proved that the micro electrochemical milling with nanosecond pulse technique is an effective machining method to fabricate metal microstructures.

The change of crowd energy is a fundamental measurement for describing a crowd behavior. In this paper, we present a crowd abnormal detection method based on the change of energy-level distribution. The method can not only reduce the camera perspective effect, but also detect crowd abnormal behavior in time. Pixels in the image are treated as particles, and the optical flow method is adopted to extract the velocities of particles. The qualities of different particles are distributed as different value according to the distance between the particle and the camera to reduce the camera perspective effect. Then a crowd motion segmentation method based on flow field texture representation is utilized to extract the motion foreground, and a linear interpolation calculation is applied to pedestrian’s foreground area to determine their distance to the camera. This contributes to the calculation of the particle qualities in different locations. Finally, the crowd behavior is analyzed according to the change of the consistency, entropy and contrast of the three descriptors for co-occurrence matrix. By calculating a threshold, the timestamp when the crowd abnormal happens is determined. In this paper, multiple sets of videos from three different scenes in UMN dataset are employed in the experiment. The results show that the proposed method is effective in characterizing anomalies in videos.

The human face plays an important role in our social interaction, conveying people’s identity. Using the human face as a key to security, biometric passwords technology has received significant attention in the past several years due to its potential for a wide variety of applications. Faces can have many variations in appearance (aging, facial expression, illumination, inaccurate alignment and pose) which continue to cause poor ability to recognize identity. The purpose of our research work is to provide an approach that contributes to resolve face identification issues with large variations of parameters such as pose, illumination, and expression. For provable outcomes, we combined two algorithms: (a) robustness local binary pattern (LBP), used for facial feature extractions; (b) k-nearest neighbor (K-NN) for image classifications. Our experiment has been conducted on the CMU PIE (Carnegie Mellon University Pose, Illumination, and Expression) face database and the LFW (Labeled Faces in the Wild) dataset. The proposed identification system shows higher performance, and also provides successful face similarity measures focus on feature extractions.