Metal Additive Manufacturing(MAM) technology has become an important means of rapid prototyping precision manufacturing of special high dynamic heterogeneous complex parts. In response to the micromechanical defects s...Metal Additive Manufacturing(MAM) technology has become an important means of rapid prototyping precision manufacturing of special high dynamic heterogeneous complex parts. In response to the micromechanical defects such as porosity issues, significant deformation, surface cracks, and challenging control of surface morphology encountered during the selective laser melting(SLM) additive manufacturing(AM) process of specialized Micro Electromechanical System(MEMS) components, multiparameter optimization and micro powder melt pool/macro-scale mechanical properties control simulation of specialized components are conducted. The optimal parameters obtained through highprecision preparation and machining of components and static/high dynamic verification are: laser power of 110 W, laser speed of 600 mm/s, laser diameter of 75 μm, and scanning spacing of 50 μm. The density of the subordinate components under this reference can reach 99.15%, the surface hardness can reach 51.9 HRA, the yield strength can reach 550 MPa, the maximum machining error of the components is 4.73%, and the average surface roughness is 0.45 μm. Through dynamic hammering and high dynamic firing verification, SLM components meet the requirements for overload resistance. The results have proven that MEM technology can provide a new means for the processing of MEMS components applied in high dynamic environments. The parameters obtained in the conclusion can provide a design basis for the additive preparation of MEMS components.展开更多
3D printing technology enhances the combustion characteristics of hybrid rocket fuels by enabling complex geometries. However, improvements in regression rates and energy properties of monotonous 3D printed fuels have...3D printing technology enhances the combustion characteristics of hybrid rocket fuels by enabling complex geometries. However, improvements in regression rates and energy properties of monotonous 3D printed fuels have been limited. This study explores the impact of poly(vinylidene fluoride) and polydopamine-coated aluminum particles on the thermal and combustion properties of 3D printed hybrid rocket fuels. Physical self-assembly and anti-solvent methods were employed for constructing composite μAl particles. Characterization using SEM, XRD, XPS, FTIR, and μCT revealed a core-shell structure and homogeneous elemental distribution. Thermal analysis showed that PVDF coatings significantly increased the heat of combustion for aluminum particles, with maximum enhancement observed in μAl@PDA@PVDF(denoted as μAl@PF) at 6.20 k J/g. Subsequently, 3D printed fuels with varying pure and composite μAl particle contents were prepared using 3D printing. Combustion tests indicated higher regression rates for Al@PF/Resin composites compared to pure resin, positively correlating with particle content. The fluorocarbon-alumina reaction during the combustion stage intensified Al particle combustion, reducing residue size. A comprehensive model based on experiments provides insights into the combustion process of PDA and PVDF-coated droplets. This study advances the design of 3D-printed hybrid rocket fuels, offering strategies to improve regression rates and energy release, crucial for enhancing solid fuel performance for hybrid propulsion.展开更多
Range-azimuth imaging of ground targets via frequency-modulated continuous wave(FMCW)radar is crucial for effective target detection.However,when the pitch of the moving array constructed during motion exceeds the phy...Range-azimuth imaging of ground targets via frequency-modulated continuous wave(FMCW)radar is crucial for effective target detection.However,when the pitch of the moving array constructed during motion exceeds the physical array aperture,azimuth ambiguity occurs,making range-azimuth imaging on a moving platform challenging.To address this issue,we theoretically analyze azimuth ambiguity generation in sparse motion arrays and propose a dual-aperture adaptive processing(DAAP)method for suppressing azimuth ambiguity.This method combines spatial multiple-input multiple-output(MIMO)arrays with sparse motion arrays to achieve high-resolution range-azimuth imaging.In addition,an adaptive QR decomposition denoising method for sparse array signals based on iterative low-rank matrix approximation(LRMA)and regularized QR is proposed to preprocess sparse motion array signals.Simulations and experiments show that on a two-transmitter-four-receiver array,the signal-to-noise ratio(SNR)of the sparse motion array signal after noise suppression via adaptive QR decomposition can exceed 0 dB,and the azimuth ambiguity signal ratio(AASR)can be reduced to below-20 dB.展开更多
System upgrades in unmanned systems have made Unmanned Aerial Vehicle(UAV)-based patrolling and monitoring a preferred solution for ocean surveillance.However,dynamic environments and large-scale deployments pose sign...System upgrades in unmanned systems have made Unmanned Aerial Vehicle(UAV)-based patrolling and monitoring a preferred solution for ocean surveillance.However,dynamic environments and large-scale deployments pose significant challenges for efficient decision-making,necessitating a modular multiagent control system.Deep Reinforcement Learning(DRL)and Decision Tree(DT)have been utilized for these complex decision-making tasks,but each has its limitations:DRL is highly adaptive but lacks interpretability,while DT is inherently interpretable but has limited adaptability.To overcome these challenges,we propose the Adaptive Interpretable Decision Tree(AIDT),an evolutionary-based algorithm that is both adaptable to diverse environmental settings and highly interpretable in its decision-making processes.We first construct a Markov decision process(MDP)-based simulation environment using the Cooperative Submarine Search task as a representative scenario for training and testing the proposed method.Specifically,we use the heat map as a state variable to address the issue of multi-agent input state proliferation.Next,we introduce the curiosity-guiding intrinsic reward to encourage comprehensive exploration and enhance algorithm performance.Additionally,we incorporate decision tree size as an influence factor in the adaptation process to balance task completion with computational efficiency.To further improve the generalization capability of the decision tree,we apply a normalization method to ensure consistent processing of input states.Finally,we validate the proposed algorithm in different environmental settings,and the results demonstrate both its adaptability and interpretability.展开更多
The operational readiness test(ORT),like weapon testing before firing,is becoming more and more important for systems used in the field.However,the test requirement of the ORT is distinctive.Specifically,the rule of s...The operational readiness test(ORT),like weapon testing before firing,is becoming more and more important for systems used in the field.However,the test requirement of the ORT is distinctive.Specifically,the rule of selecting test items should be changed in different test turns,and whether there is a fault is more important than where the fault is.The popular dependency matrix(D-matrix)processing algorithms becomes low efficient because they cannot change their optimizing direc-tion and spend unnecessary time on fault localization and isola-tion.To this end,this paper proposes a D-matrix processing algorithm named piecewise heuristic algorithm for D-matrix(PHAD).Its key idea is to use a piecewise function comprised of multiple different functions instead of the commonly used fixed function and switch subfunctions according to the test stage.In this manner,PHAD has the capability of changing optimizing direction,precisely matching the variant test requirements,and generating an efficient test sequence.The experiments on the random matrixes of different sizes and densities prove that the proposed algorithm performs better than the classical algo-rithms in terms of expected test cost(ETC)and other metrics.More generally,the piecewise heuristic function shows a new way to design D-matrix processing algorithm and a more flexi-ble heuristic function to meet more complicated test requirements.展开更多
Urban air pollution has brought great troubles to physical and mental health,economic development,environmental protection,and other aspects.Predicting the changes and trends of air pollution can provide a scientific ...Urban air pollution has brought great troubles to physical and mental health,economic development,environmental protection,and other aspects.Predicting the changes and trends of air pollution can provide a scientific basis for governance and prevention efforts.In this paper,we propose an interval prediction method that considers the spatio-temporal characteristic information of PM_(2.5)signals from multiple stations.K-nearest neighbor(KNN)algorithm interpolates the lost signals in the process of collection,transmission,and storage to ensure the continuity of data.Graph generative network(GGN)is used to process time-series meteorological data with complex structures.The graph U-Nets framework is introduced into the GGN model to enhance its controllability to the graph generation process,which is beneficial to improve the efficiency and robustness of the model.In addition,sparse Bayesian regression is incorporated to improve the dimensional disaster defect of traditional kernel density estimation(KDE)interval prediction.With the support of sparse strategy,sparse Bayesian regression kernel density estimation(SBR-KDE)is very efficient in processing high-dimensional large-scale data.The PM_(2.5)data of spring,summer,autumn,and winter from 34 air quality monitoring sites in Beijing verified the accuracy,generalization,and superiority of the proposed model in interval prediction.展开更多
The impact safety of explosive charges has been focused in these decades. The fragment impact is widely used to evaluate the response of explosive charges. In our work, the explosive detonation driving technique was u...The impact safety of explosive charges has been focused in these decades. The fragment impact is widely used to evaluate the response of explosive charges. In our work, the explosive detonation driving technique was used to generate a high velocity fragment with large mass. When the fragment masses are10 g, 16 g, 25 g, and 50 g, the highest velocity of fragments can reach 2400 m/s, 2100 m/s, 1900 m/s, and1400 m/s, respectively. The high velocity fragment with large mass was used to evaluate the safety of two kinds of CL-20 based explosive charges. The effects of the fragment mass and velocity were analyzed.Especially, the reaction extent was obtained based on visible phenomenon. The CL-20-based explosive charge containing Al had a higher safety level than that without Al. It was because Al had good ductility,and further improved the mechanical property of the material. Also, the numerical simulation was conducted to understand the reaction characteristics of the CL-20-based explosive charge. The results showed that as the fragment mass and velocity increased, the reaction became more violent.展开更多
Aluminum(Al)powder is widely applied in thermobaric explosives due to its high energy density and favorable reaction kinetics.However,the inert oxide layer(Al_(2)O_(3))on Al particles limits combustion reactivity and ...Aluminum(Al)powder is widely applied in thermobaric explosives due to its high energy density and favorable reaction kinetics.However,the inert oxide layer(Al_(2)O_(3))on Al particles limits combustion reactivity and energy efficiency.Fluoride-based surface modification has been developed as an effective approach to address this issue.Here,four classical fluoropolymers(F11,F14,PVDF,PTFE)are employed as coatings to prepare core-shell Al/Fluoropolymer.The combustion experimental results demonstrate that the core-shell Al/PTFE exhibits the highest flame propagation rate(52.88 mm·ms^(-1))and pressure output(109.02 k Pa)performance.Consequently,core-shell Al/PTFE is selected as a high-energy fuel to prepare RDX/Al/PTFE microspheres via the emulsion and solvent evaporation method,which can enhance the energy performance of RDX.The effects of the core-shell Al/PTFE ratio and RDX content on the combustion heat and pressure output are systematically investigated.The peak pressure reaches a maximum of 187.8 k Pa when the mass ratio of RDX,Al,and PTFE is 60:25:10.Additionally,RDX/Al/PTFE microspheres exhibit significantly higher laser-induced air shock velocities,detonation heat,and detonation pressure than those of pure RDX and RDX/Al.The mechanism underlying the enhanced reactivity and energetic performance is attributed to the ability of PTFE to etch the inert Al_(2)O_(3)shell on the surface of Al particles,thereby improving post-combustion reactions and significantly increasing the overall energy output of RDX explosives.This work offers a novel design strategy for high-energy structural thermobaric explosives for the practical applications.展开更多
A typical Whipple shield consists of double-layered plates with a certain gap.The space debris impacts the outer plate and is broken into a debris cloud(shattered,molten,vaporized)with dispersed energy and momentum,wh...A typical Whipple shield consists of double-layered plates with a certain gap.The space debris impacts the outer plate and is broken into a debris cloud(shattered,molten,vaporized)with dispersed energy and momentum,which reduces the risk of penetrating the bulkhead.In the realm of hypervelocity impact,strain rate(>10^(5)s^(-1))effects are negligible,and fluid dynamics is employed to describe the impact process.Efficient numerical tools for precisely predicting the damage degree can greatly accelerate the design and optimization of advanced protective structures.Current hypervelocity impact research primarily focuses on the interaction between projectile and front plate and the movement of debris cloud.However,the damage mechanism of debris cloud impacts on rear plates-the critical threat component-remains underexplored owing to complex multi-physics processes and prohibitive computational costs.Existing approaches,ranging from semi-empirical equations to a machine learningbased ballistic limit prediction method,are constrained to binary penetration classification.Alternatively,the uneven data from experiments and simulations caused these methods to be ineffective when the projectile has irregular shapes and complicate flight attitude.Therefore,it is urgent to develop a new damage prediction method for predicting the rear plate damage,which can help to gain a deeper understanding of the damage mechanism.In this study,a machine learning(ML)method is developed to predict the damage distribution in the rear plate.Based on the unit velocity space,the discretized information of debris cloud and rear plate damage from rare simulation cases is used as input data for training the ML models,while the generalization ability for damage distribution prediction is tested by other simulation cases with different attack angles.The results demonstrate that the training and prediction accuracies using the Random Forest(RF)algorithm significantly surpass those using Artificial Neural Networks(ANNs)and Support Vector Machine(SVM).The RF-based model effectively identifies damage features in sparsely distributed debris cloud and cumulative effect.This study establishes an expandable new dataset that accommodates additional parameters to improve the prediction accuracy.Results demonstrate the model's ability to overcome data imbalance limitations through debris cloud features,enabling rapid and accurate rear plate damage prediction across wider scenarios with minimal data requirements.展开更多
This study investigates the paradoxical detonation behavior of TKX-50,a nitrogen-rich energetic material,exhibiting higher detonation velocities but lower metal acceleration ability compared to HMX.Through experimenta...This study investigates the paradoxical detonation behavior of TKX-50,a nitrogen-rich energetic material,exhibiting higher detonation velocities but lower metal acceleration ability compared to HMX.Through experimental measurements and theoretical calculations,we propose a novel three-factor competition mechanism to explain this phenomenon.TKX-50-based PBX formulations achieved detonation velocities up to 9100 m/s,surpassing HMX-based counterparts.However,cylinder expansion tests revealed a 15%reduction in metal acceleration ability.Thermochemical measurements showed lower detonation heat for TKX-50(4900 J/g)versus HMX(5645 J/g).Our mechanism involves:(1)compositional effects prevailing at high pressures;(2)Energy release becoming essential as pressure drops;(3)Pressure-dependent product composition evolution functioning at low pressure.VLW code calculations unveiled a"crossover"in Hugoniot curves,lending support to this mechanism.This study furnishes a new framework for comprehending the performance of nitrogen-rich energetic materials,with significant implications for the design and optimization of future high-energy density materials.展开更多
CAB is a binder commonly utilized in CL-20-based mixed explosives.Based on the requirements of CL-20-based polymer bonded explosives in formability,safety,and detonation energy,we explored a hightoughness and low dosa...CAB is a binder commonly utilized in CL-20-based mixed explosives.Based on the requirements of CL-20-based polymer bonded explosives in formability,safety,and detonation energy,we explored a hightoughness and low dosage CAB binder system.CAB was subjected to different toughening modifications and the effects of the modified CAB binders on the bonding and coating of CL-20 crystals,as well as the formability,safety,and mechanical properties of CL-20-based polymer bonded explosive molding powder(MP)were evaluated.The changes in glass transition temperature(Tg)and mechanical properties of the modified binders were investigated using the molecular dynamics simulation at first.A series of modified binders with different molecular weights were then synthesized and characterized by FTIR,1H NMR,^(13)C NMR and SEC.The T_(g) and cross-sectional morphologies of the binder membranes were determined by DSC and SEM.The tensile properties of the binder membranes with different molecular weights and their mixtures with the plasticizer were evaluated at different temperature.With the optimized modified binder,CL-20/CAB and CL-20/CAB-g-PCL-3 MPs with the same plasticizer ratio and Cl-20/CAB-g-PCL-3 MP with a lower plasticizer ratio and higher CL-20 content were prepared and evaluated for the bonding and coating effects,crystal form,mechanical sensitivity and specific heat capacity(C_(p))by SEM,XRD,sensitivity testing and DSC,respectively.Their compressive strengths and splitting tensile strengths were measured at different temperature using a universal testing machine.Our work has provided a high-toughness and low-dosage binder system for CL-20-based MPs and offers a novel strategy to improve the formability,safety,and energy of CL-20 based polymer bonded explosives.展开更多
Passive bionic feet,known for their human-like compliance,have garnered attention for their potential to achieve notable environmental adaptability.In this paper,a method was proposed to unifying passive bionic feet s...Passive bionic feet,known for their human-like compliance,have garnered attention for their potential to achieve notable environmental adaptability.In this paper,a method was proposed to unifying passive bionic feet static supporting stability and dynamic terrain adaptability through the utilization of the Rigid-Elastic Hybrid(REH)dynamics model.First,a bionic foot model,named the Hinge Tension Elastic Complex(HTEC)model,was developed by extracting key features from human feet.Furthermore,the kinematics and REH dynamics of the HTEC model were established.Based on the foot dynamics,a nonlinear optimization method for stiffness matching(NOSM)was designed.Finally,the HTEC-based foot was constructed and applied onto BHR-B2 humanoid robot.The foot static stability is achieved.The enhanced adaptability is observed as the robot traverses square steel,lawn,and cobblestone terrains.Through proposed design method and structure,the mobility of the humanoid robot is improved.展开更多
In the present study,two-layered stainless steel-copper composites with a thickness of 50μm were initially subjected to annealing at 800,900 and 1000℃for 5 min,respectively,to achieve diverse microstructural feature...In the present study,two-layered stainless steel-copper composites with a thickness of 50μm were initially subjected to annealing at 800,900 and 1000℃for 5 min,respectively,to achieve diverse microstructural features.Then the influence of annealing temperature on the formability of stainless steel-copper composites and the quality of micro composite cups manufactured by micro deep drawing(MDD)were investigated,and the underlying mechanism was analyzed.Three finite element(FE)models,including basic FE model,Voronoi FE model and surface morphological FE model,were developed to analyze the forming performance of stainless steel-copper composites during MDD.The results show that the stainless steel-copper composites annealed at 900℃possess the best plasticity owing to the homogeneous and refined microstructure in both stainless steel and copper matrixes,and the micro composite cup with specimen annealed at 900℃exhibits a uniform wall thickness as well as high surface quality with the fewest wrinkles.The results obtained from the surface morphological FE model considering material inhomogeneity and surface morphology of the composites are the closest to the experimental results compared to the basic and Voronoi FE model.During MDD process,the drawing forces decrease with increasing annealing temperature as a consequence of the strength reduction.展开更多
LuGre model has been widely used in friction modeling and compensation.However,the new friction regime,named prestiction regime,cannot be accurately characterized by LuGre model in the latest research.With the extensi...LuGre model has been widely used in friction modeling and compensation.However,the new friction regime,named prestiction regime,cannot be accurately characterized by LuGre model in the latest research.With the extensive experimental observations of friction behaviors in the prestiction,some variables were abstracted to depict the rules in the prestiction regime.Based upon the knowledge of friction modeling,a novel friction model including the presliding regime,the gross sliding regime and the prestiction regime was then presented to overcome the shortcomings of the LuGre model.The reason that LuGre model cannot estimate the prestiction friction was analyzed in theory.Feasibility analysis of the proposed model in modeling the prestiction friction was also addressed.A parameter identification method for the proposed model based on multilevel coordinate search algorithm was presented.The proposed friction compensation strategy was composed of a nonlinear friction observer and a feedforward mechanism.The friction observer was designed to estimate the friction force in the presliding and the gross sliding regimes.And the friction force was estimated based on the model in the prestiction regime.The comparative trajectory tracking experiments were conducted on a simulator of inertially stabilization platforms among three control schemes:the single proportional–derivative(PD)control,the PD with LuGre model-based compensation and the PD with compensator based on the presented model.The experimental results reveal that the control scheme based on the proposed model has the best tracking performance.It reduces the peak-to-peak value(PPV)of tracking error to 0.2 mrad,which is improved almost 50%compared with the PD with LuGre model-based compensation.Compared to the single PD control,it reduces the PPV of error by 66.7%.展开更多
The infrared conformal window is one of the most critical components in aircraft.Conformal windows with high performance bring low aberrations,high aerodynamic performance,reliability in extreme working environments,a...The infrared conformal window is one of the most critical components in aircraft.Conformal windows with high performance bring low aberrations,high aerodynamic performance,reliability in extreme working environments,and added value for aircraft.Through the past decades,remarkable advances have been achieved in manufacturing technologies for conformal windows,where the machining accuracy approaches the nanometer level,and the surface form becomes more complex.These advances are critical to aircraft development,and these manufacturing technologies also have significant reference values for other directions of the ultra-precision machining field.In this review,the infrared materials suitable for manufacturing conformal windows are introduced and compared with insights into their performances.The remarkable advances and concrete work accomplished by researchers are reviewed.The challenges in manufacturing conformal windows that should be faced in the future are discussed.展开更多
The longitudinal dispersion of the projectile in shooting tests of two-dimensional trajectory corrections fused with fixed canards is extremely large that it sometimes exceeds the correction ability of the correction ...The longitudinal dispersion of the projectile in shooting tests of two-dimensional trajectory corrections fused with fixed canards is extremely large that it sometimes exceeds the correction ability of the correction fuse actuator.The impact point easily deviates from the target,and thus the correction result cannot be readily evaluated.However,the cost of shooting tests is considerably high to conduct many tests for data collection.To address this issue,this study proposes an aiming method for shooting tests based on small sample size.The proposed method uses the Bootstrap method to expand the test data;repeatedly iterates and corrects the position of the simulated theoretical impact points through an improved compatibility test method;and dynamically adjusts the weight of the prior distribution of simulation results based on Kullback-Leibler divergence,which to some extent avoids the real data being"submerged"by the simulation data and achieves the fusion Bayesian estimation of the dispersion center.The experimental results show that when the simulation accuracy is sufficiently high,the proposed method yields a smaller mean-square deviation in estimating the dispersion center and higher shooting accuracy than those of the three comparison methods,which is more conducive to reflecting the effect of the control algorithm and facilitating test personnel to iterate their proposed structures and algorithms.;in addition,this study provides a knowledge base for further comprehensive studies in the future.展开更多
To solve the problem of the low interference success rate of air defense missile radio fuzes due to the unified interference form of the traditional fuze interference system,an interference decision method based Q-lea...To solve the problem of the low interference success rate of air defense missile radio fuzes due to the unified interference form of the traditional fuze interference system,an interference decision method based Q-learning algorithm is proposed.First,dividing the distance between the missile and the target into multiple states to increase the quantity of state spaces.Second,a multidimensional motion space is utilized,and the search range of which changes with the distance of the projectile,to select parameters and minimize the amount of ineffective interference parameters.The interference effect is determined by detecting whether the fuze signal disappears.Finally,a weighted reward function is used to determine the reward value based on the range state,output power,and parameter quantity information of the interference form.The effectiveness of the proposed method in selecting the range of motion space parameters and designing the discrimination degree of the reward function has been verified through offline experiments involving full-range missile rendezvous.The optimal interference form for each distance state has been obtained.Compared with the single-interference decision method,the proposed decision method can effectively improve the success rate of interference.展开更多
In order to improve the energy output consistency of 3, 3’-diamino-4, 4’-azoxyfurazan(DAAF) in the new insensitive booster and the safety and efficiency in the preparation process, a continuous preparation system of...In order to improve the energy output consistency of 3, 3’-diamino-4, 4’-azoxyfurazan(DAAF) in the new insensitive booster and the safety and efficiency in the preparation process, a continuous preparation system of DAAF from synthesis to spherical coating was designed and established in this paper, which combined ultrasonic micromixing reaction with microdroplet globular template. In the rapid micromixing stage, the microfluidic mixing technology with ultrasonic was used to synergistically strengthen the uniform and rapid mass transfer mixing reaction between raw materials to ensure the uniformity of DAAF particle nucleation-growth, and to prepare high-quality DAAF crystals with uniform structure and morphology and concentrated particle size distribution. In the microdroplet globular template stage, the microfluidic droplet technology was used to form a droplet globular template with uniform size under the shear action of the continuous phase of the dispersed phase solution containing DAAF particles and binder. The size of the droplet template was controlled by adjusting the flow rate ratio between the continuous phase and the dispersed phase. In the droplet globular template, with the diffusion of the solvent in the dispersed phase droplets, the binder precipitates to coat the DAAF into a ball, forming a DAAF microsphere with high sphericity, narrow particle size distribution and good monodispersity. The problem of discontinuity and DAAF particle suspension in the process was solved, and the coating theory under this process was studied. DAAF was coated with different binder formulations of fluororubber(F2604), nitrocellulose(NC) and NC/glycidyl azide polymer(GAP), and the process verification and evaluation of the system were carried out. The balling effects of large, medium and small droplet templates under different binder formulations were studied. The scanning electron microscope(SEM) results show that the three droplet templates under the three binder formulations exhibit good balling effect and narrow particle size distribution. The DAAF microspheres were characterized by powder X-ray diffraction(XRD), differential scanning calorimetry(DSC), thermo-gravimetric(TG) and sensitivity analyzer. The results showed that the crystal structure of DAAF did not change during the process, and the prepared DAAF microspheres had lower decomposition temperature and lower mechanical sensitivity than raw DAAF. The results of detonation parameters show that the coating of DAAF by using the above three binder formulations will not greatly reduce the energy output of DAAF, and has comparable detonation performance to raw DAAF. This study proves an efficient and safe continuous system from synthesis to spherical coating modification of explosives, which provides a new way for the continuous, safe and efficient preparation of spherical explosives.展开更多
The identification of intercepted radio fuze modulation types is a prerequisite for decision-making in interference systems.However,the electromagnetic environment of modern battlefields is complex,and the signal-to-n...The identification of intercepted radio fuze modulation types is a prerequisite for decision-making in interference systems.However,the electromagnetic environment of modern battlefields is complex,and the signal-to-noise ratio(SNR)of such environments is usually low,which makes it difficult to implement accurate recognition of radio fuzes.To solve the above problem,a radio fuze automatic modulation recognition(AMR)method for low-SNR environments is proposed.First,an adaptive denoising algorithm based on data rearrangement and the two-dimensional(2D)fast Fourier transform(FFT)(DR2D)is used to reduce the noise of the intercepted radio fuze intermediate frequency(IF)signal.Then,the textural features of the denoised IF signal rearranged data matrix are extracted from the statistical indicator vectors of gray-level cooccurrence matrices(GLCMs),and support vector machines(SVMs)are used for classification.The DR2D-based adaptive denoising algorithm achieves an average correlation coefficient of more than 0.76 for ten fuze types under SNRs of-10 d B and above,which is higher than that of other typical algorithms.The trained SVM classification model achieves an average recognition accuracy of more than 96%on seven modulation types and recognition accuracies of more than 94%on each modulation type under SNRs of-12 d B and above,which represents a good AMR performance of radio fuzes under low SNRs.展开更多
Uniform linear array(ULA)radars are widely used in the collision-avoidance radar systems of small unmanned aerial vehicles(UAVs).In practice,a ULA's multi-target direction of arrival(DOA)estimation performance suf...Uniform linear array(ULA)radars are widely used in the collision-avoidance radar systems of small unmanned aerial vehicles(UAVs).In practice,a ULA's multi-target direction of arrival(DOA)estimation performance suffers from significant performance degradation owing to the limited number of physical elements.To improve the underdetermined DOA estimation performance of a ULA radar mounted on a small UAV platform,we propose a nonuniform linear motion sampling underdetermined DOA estimation method.Using the motion of the UAV platform,the echo signal is sampled at different positions.Then,according to the concept of difference co-array,a virtual ULA with multiple array elements and a large aperture is synthesized to increase the degrees of freedom(DOFs).Through position analysis of the original and motion arrays,we propose a nonuniform linear motion sampling method based on ULA for determining the optimal DOFs.Under the condition of no increase in the aperture of the physical array,the proposed method obtains a high DOF with fewer sampling runs and greatly improves the underdetermined DOA estimation performance of ULA.The results of numerical simulations conducted herein verify the superior performance of the proposed method.展开更多
基金funded by the National Natural Science Foundation of China Youth Fund(Grant No.62304022)Science and Technology on Electromechanical Dynamic Control Laboratory(China,Grant No.6142601012304)the 2022e2024 China Association for Science and Technology Innovation Integration Association Youth Talent Support Project(Grant No.2022QNRC001).
文摘Metal Additive Manufacturing(MAM) technology has become an important means of rapid prototyping precision manufacturing of special high dynamic heterogeneous complex parts. In response to the micromechanical defects such as porosity issues, significant deformation, surface cracks, and challenging control of surface morphology encountered during the selective laser melting(SLM) additive manufacturing(AM) process of specialized Micro Electromechanical System(MEMS) components, multiparameter optimization and micro powder melt pool/macro-scale mechanical properties control simulation of specialized components are conducted. The optimal parameters obtained through highprecision preparation and machining of components and static/high dynamic verification are: laser power of 110 W, laser speed of 600 mm/s, laser diameter of 75 μm, and scanning spacing of 50 μm. The density of the subordinate components under this reference can reach 99.15%, the surface hardness can reach 51.9 HRA, the yield strength can reach 550 MPa, the maximum machining error of the components is 4.73%, and the average surface roughness is 0.45 μm. Through dynamic hammering and high dynamic firing verification, SLM components meet the requirements for overload resistance. The results have proven that MEM technology can provide a new means for the processing of MEMS components applied in high dynamic environments. The parameters obtained in the conclusion can provide a design basis for the additive preparation of MEMS components.
基金funded by the National Natural Science Foundation of China(Grant No.06101213)the National Natural Science Foundation of China(Grant No.22105160).
文摘3D printing technology enhances the combustion characteristics of hybrid rocket fuels by enabling complex geometries. However, improvements in regression rates and energy properties of monotonous 3D printed fuels have been limited. This study explores the impact of poly(vinylidene fluoride) and polydopamine-coated aluminum particles on the thermal and combustion properties of 3D printed hybrid rocket fuels. Physical self-assembly and anti-solvent methods were employed for constructing composite μAl particles. Characterization using SEM, XRD, XPS, FTIR, and μCT revealed a core-shell structure and homogeneous elemental distribution. Thermal analysis showed that PVDF coatings significantly increased the heat of combustion for aluminum particles, with maximum enhancement observed in μAl@PDA@PVDF(denoted as μAl@PF) at 6.20 k J/g. Subsequently, 3D printed fuels with varying pure and composite μAl particle contents were prepared using 3D printing. Combustion tests indicated higher regression rates for Al@PF/Resin composites compared to pure resin, positively correlating with particle content. The fluorocarbon-alumina reaction during the combustion stage intensified Al particle combustion, reducing residue size. A comprehensive model based on experiments provides insights into the combustion process of PDA and PVDF-coated droplets. This study advances the design of 3D-printed hybrid rocket fuels, offering strategies to improve regression rates and energy release, crucial for enhancing solid fuel performance for hybrid propulsion.
基金supported by the National Natural Science Foundation of China under Grant 62301051.
文摘Range-azimuth imaging of ground targets via frequency-modulated continuous wave(FMCW)radar is crucial for effective target detection.However,when the pitch of the moving array constructed during motion exceeds the physical array aperture,azimuth ambiguity occurs,making range-azimuth imaging on a moving platform challenging.To address this issue,we theoretically analyze azimuth ambiguity generation in sparse motion arrays and propose a dual-aperture adaptive processing(DAAP)method for suppressing azimuth ambiguity.This method combines spatial multiple-input multiple-output(MIMO)arrays with sparse motion arrays to achieve high-resolution range-azimuth imaging.In addition,an adaptive QR decomposition denoising method for sparse array signals based on iterative low-rank matrix approximation(LRMA)and regularized QR is proposed to preprocess sparse motion array signals.Simulations and experiments show that on a two-transmitter-four-receiver array,the signal-to-noise ratio(SNR)of the sparse motion array signal after noise suppression via adaptive QR decomposition can exceed 0 dB,and the azimuth ambiguity signal ratio(AASR)can be reduced to below-20 dB.
文摘System upgrades in unmanned systems have made Unmanned Aerial Vehicle(UAV)-based patrolling and monitoring a preferred solution for ocean surveillance.However,dynamic environments and large-scale deployments pose significant challenges for efficient decision-making,necessitating a modular multiagent control system.Deep Reinforcement Learning(DRL)and Decision Tree(DT)have been utilized for these complex decision-making tasks,but each has its limitations:DRL is highly adaptive but lacks interpretability,while DT is inherently interpretable but has limited adaptability.To overcome these challenges,we propose the Adaptive Interpretable Decision Tree(AIDT),an evolutionary-based algorithm that is both adaptable to diverse environmental settings and highly interpretable in its decision-making processes.We first construct a Markov decision process(MDP)-based simulation environment using the Cooperative Submarine Search task as a representative scenario for training and testing the proposed method.Specifically,we use the heat map as a state variable to address the issue of multi-agent input state proliferation.Next,we introduce the curiosity-guiding intrinsic reward to encourage comprehensive exploration and enhance algorithm performance.Additionally,we incorporate decision tree size as an influence factor in the adaptation process to balance task completion with computational efficiency.To further improve the generalization capability of the decision tree,we apply a normalization method to ensure consistent processing of input states.Finally,we validate the proposed algorithm in different environmental settings,and the results demonstrate both its adaptability and interpretability.
文摘The operational readiness test(ORT),like weapon testing before firing,is becoming more and more important for systems used in the field.However,the test requirement of the ORT is distinctive.Specifically,the rule of selecting test items should be changed in different test turns,and whether there is a fault is more important than where the fault is.The popular dependency matrix(D-matrix)processing algorithms becomes low efficient because they cannot change their optimizing direc-tion and spend unnecessary time on fault localization and isola-tion.To this end,this paper proposes a D-matrix processing algorithm named piecewise heuristic algorithm for D-matrix(PHAD).Its key idea is to use a piecewise function comprised of multiple different functions instead of the commonly used fixed function and switch subfunctions according to the test stage.In this manner,PHAD has the capability of changing optimizing direction,precisely matching the variant test requirements,and generating an efficient test sequence.The experiments on the random matrixes of different sizes and densities prove that the proposed algorithm performs better than the classical algo-rithms in terms of expected test cost(ETC)and other metrics.More generally,the piecewise heuristic function shows a new way to design D-matrix processing algorithm and a more flexi-ble heuristic function to meet more complicated test requirements.
基金Project(2020YFC2008605)supported by the National Key Research and Development Project of ChinaProject(52072412)supported by the National Natural Science Foundation of ChinaProject(2021JJ30359)supported by the Natural Science Foundation of Hunan Province,China。
文摘Urban air pollution has brought great troubles to physical and mental health,economic development,environmental protection,and other aspects.Predicting the changes and trends of air pollution can provide a scientific basis for governance and prevention efforts.In this paper,we propose an interval prediction method that considers the spatio-temporal characteristic information of PM_(2.5)signals from multiple stations.K-nearest neighbor(KNN)algorithm interpolates the lost signals in the process of collection,transmission,and storage to ensure the continuity of data.Graph generative network(GGN)is used to process time-series meteorological data with complex structures.The graph U-Nets framework is introduced into the GGN model to enhance its controllability to the graph generation process,which is beneficial to improve the efficiency and robustness of the model.In addition,sparse Bayesian regression is incorporated to improve the dimensional disaster defect of traditional kernel density estimation(KDE)interval prediction.With the support of sparse strategy,sparse Bayesian regression kernel density estimation(SBR-KDE)is very efficient in processing high-dimensional large-scale data.The PM_(2.5)data of spring,summer,autumn,and winter from 34 air quality monitoring sites in Beijing verified the accuracy,generalization,and superiority of the proposed model in interval prediction.
文摘The impact safety of explosive charges has been focused in these decades. The fragment impact is widely used to evaluate the response of explosive charges. In our work, the explosive detonation driving technique was used to generate a high velocity fragment with large mass. When the fragment masses are10 g, 16 g, 25 g, and 50 g, the highest velocity of fragments can reach 2400 m/s, 2100 m/s, 1900 m/s, and1400 m/s, respectively. The high velocity fragment with large mass was used to evaluate the safety of two kinds of CL-20 based explosive charges. The effects of the fragment mass and velocity were analyzed.Especially, the reaction extent was obtained based on visible phenomenon. The CL-20-based explosive charge containing Al had a higher safety level than that without Al. It was because Al had good ductility,and further improved the mechanical property of the material. Also, the numerical simulation was conducted to understand the reaction characteristics of the CL-20-based explosive charge. The results showed that as the fragment mass and velocity increased, the reaction became more violent.
基金supported by the National Natural Science Foundation of China(Grant Nos.T2222027 and 12202416)。
文摘Aluminum(Al)powder is widely applied in thermobaric explosives due to its high energy density and favorable reaction kinetics.However,the inert oxide layer(Al_(2)O_(3))on Al particles limits combustion reactivity and energy efficiency.Fluoride-based surface modification has been developed as an effective approach to address this issue.Here,four classical fluoropolymers(F11,F14,PVDF,PTFE)are employed as coatings to prepare core-shell Al/Fluoropolymer.The combustion experimental results demonstrate that the core-shell Al/PTFE exhibits the highest flame propagation rate(52.88 mm·ms^(-1))and pressure output(109.02 k Pa)performance.Consequently,core-shell Al/PTFE is selected as a high-energy fuel to prepare RDX/Al/PTFE microspheres via the emulsion and solvent evaporation method,which can enhance the energy performance of RDX.The effects of the core-shell Al/PTFE ratio and RDX content on the combustion heat and pressure output are systematically investigated.The peak pressure reaches a maximum of 187.8 k Pa when the mass ratio of RDX,Al,and PTFE is 60:25:10.Additionally,RDX/Al/PTFE microspheres exhibit significantly higher laser-induced air shock velocities,detonation heat,and detonation pressure than those of pure RDX and RDX/Al.The mechanism underlying the enhanced reactivity and energetic performance is attributed to the ability of PTFE to etch the inert Al_(2)O_(3)shell on the surface of Al particles,thereby improving post-combustion reactions and significantly increasing the overall energy output of RDX explosives.This work offers a novel design strategy for high-energy structural thermobaric explosives for the practical applications.
基金supported by National Natural Science Foundation of China(Grant No.12432018,12372346)the Innovative Research Groups of the National Natural Science Foundation of China(Grant No.12221002).
文摘A typical Whipple shield consists of double-layered plates with a certain gap.The space debris impacts the outer plate and is broken into a debris cloud(shattered,molten,vaporized)with dispersed energy and momentum,which reduces the risk of penetrating the bulkhead.In the realm of hypervelocity impact,strain rate(>10^(5)s^(-1))effects are negligible,and fluid dynamics is employed to describe the impact process.Efficient numerical tools for precisely predicting the damage degree can greatly accelerate the design and optimization of advanced protective structures.Current hypervelocity impact research primarily focuses on the interaction between projectile and front plate and the movement of debris cloud.However,the damage mechanism of debris cloud impacts on rear plates-the critical threat component-remains underexplored owing to complex multi-physics processes and prohibitive computational costs.Existing approaches,ranging from semi-empirical equations to a machine learningbased ballistic limit prediction method,are constrained to binary penetration classification.Alternatively,the uneven data from experiments and simulations caused these methods to be ineffective when the projectile has irregular shapes and complicate flight attitude.Therefore,it is urgent to develop a new damage prediction method for predicting the rear plate damage,which can help to gain a deeper understanding of the damage mechanism.In this study,a machine learning(ML)method is developed to predict the damage distribution in the rear plate.Based on the unit velocity space,the discretized information of debris cloud and rear plate damage from rare simulation cases is used as input data for training the ML models,while the generalization ability for damage distribution prediction is tested by other simulation cases with different attack angles.The results demonstrate that the training and prediction accuracies using the Random Forest(RF)algorithm significantly surpass those using Artificial Neural Networks(ANNs)and Support Vector Machine(SVM).The RF-based model effectively identifies damage features in sparsely distributed debris cloud and cumulative effect.This study establishes an expandable new dataset that accommodates additional parameters to improve the prediction accuracy.Results demonstrate the model's ability to overcome data imbalance limitations through debris cloud features,enabling rapid and accurate rear plate damage prediction across wider scenarios with minimal data requirements.
基金support provided by the National Natural Science Foundation of China(Grant No.12102405)the Presidential Foundation of CAEP(Grant No.YZJJZQ2023008).
文摘This study investigates the paradoxical detonation behavior of TKX-50,a nitrogen-rich energetic material,exhibiting higher detonation velocities but lower metal acceleration ability compared to HMX.Through experimental measurements and theoretical calculations,we propose a novel three-factor competition mechanism to explain this phenomenon.TKX-50-based PBX formulations achieved detonation velocities up to 9100 m/s,surpassing HMX-based counterparts.However,cylinder expansion tests revealed a 15%reduction in metal acceleration ability.Thermochemical measurements showed lower detonation heat for TKX-50(4900 J/g)versus HMX(5645 J/g).Our mechanism involves:(1)compositional effects prevailing at high pressures;(2)Energy release becoming essential as pressure drops;(3)Pressure-dependent product composition evolution functioning at low pressure.VLW code calculations unveiled a"crossover"in Hugoniot curves,lending support to this mechanism.This study furnishes a new framework for comprehending the performance of nitrogen-rich energetic materials,with significant implications for the design and optimization of future high-energy density materials.
基金supported by"the Fundamental Research Funds for the Central Universities".
文摘CAB is a binder commonly utilized in CL-20-based mixed explosives.Based on the requirements of CL-20-based polymer bonded explosives in formability,safety,and detonation energy,we explored a hightoughness and low dosage CAB binder system.CAB was subjected to different toughening modifications and the effects of the modified CAB binders on the bonding and coating of CL-20 crystals,as well as the formability,safety,and mechanical properties of CL-20-based polymer bonded explosive molding powder(MP)were evaluated.The changes in glass transition temperature(Tg)and mechanical properties of the modified binders were investigated using the molecular dynamics simulation at first.A series of modified binders with different molecular weights were then synthesized and characterized by FTIR,1H NMR,^(13)C NMR and SEC.The T_(g) and cross-sectional morphologies of the binder membranes were determined by DSC and SEM.The tensile properties of the binder membranes with different molecular weights and their mixtures with the plasticizer were evaluated at different temperature.With the optimized modified binder,CL-20/CAB and CL-20/CAB-g-PCL-3 MPs with the same plasticizer ratio and Cl-20/CAB-g-PCL-3 MP with a lower plasticizer ratio and higher CL-20 content were prepared and evaluated for the bonding and coating effects,crystal form,mechanical sensitivity and specific heat capacity(C_(p))by SEM,XRD,sensitivity testing and DSC,respectively.Their compressive strengths and splitting tensile strengths were measured at different temperature using a universal testing machine.Our work has provided a high-toughness and low-dosage binder system for CL-20-based MPs and offers a novel strategy to improve the formability,safety,and energy of CL-20 based polymer bonded explosives.
基金supported by the National Natural Science Foundation of China(Grant No.62073041)the Open Fund of Laboratory of Aerospace Servo Actuation and Transmission(Grant No.LASAT-2023A04)the Fundamental Research Funds for the Central Universities(Grant Nos.2024CX06011,2024CX06079)。
文摘Passive bionic feet,known for their human-like compliance,have garnered attention for their potential to achieve notable environmental adaptability.In this paper,a method was proposed to unifying passive bionic feet static supporting stability and dynamic terrain adaptability through the utilization of the Rigid-Elastic Hybrid(REH)dynamics model.First,a bionic foot model,named the Hinge Tension Elastic Complex(HTEC)model,was developed by extracting key features from human feet.Furthermore,the kinematics and REH dynamics of the HTEC model were established.Based on the foot dynamics,a nonlinear optimization method for stiffness matching(NOSM)was designed.Finally,the HTEC-based foot was constructed and applied onto BHR-B2 humanoid robot.The foot static stability is achieved.The enhanced adaptability is observed as the robot traverses square steel,lawn,and cobblestone terrains.Through proposed design method and structure,the mobility of the humanoid robot is improved.
基金Projects(51975398,52105392)supported by the National Natural Science Foundation of ChinaProject(YDZJSX2021A006)supported by the Central Government Guided Local Science and Technology Development Fund Project,China+1 种基金Project(20210035)supported by the Scientific Activities of Selected Returned Overseas Professionals in Shanxi Province,ChinaProject(2020-037)supported by the Fund Program for the Research Project Supported by Shanxi Scholarship Council,China。
文摘In the present study,two-layered stainless steel-copper composites with a thickness of 50μm were initially subjected to annealing at 800,900 and 1000℃for 5 min,respectively,to achieve diverse microstructural features.Then the influence of annealing temperature on the formability of stainless steel-copper composites and the quality of micro composite cups manufactured by micro deep drawing(MDD)were investigated,and the underlying mechanism was analyzed.Three finite element(FE)models,including basic FE model,Voronoi FE model and surface morphological FE model,were developed to analyze the forming performance of stainless steel-copper composites during MDD.The results show that the stainless steel-copper composites annealed at 900℃possess the best plasticity owing to the homogeneous and refined microstructure in both stainless steel and copper matrixes,and the micro composite cup with specimen annealed at 900℃exhibits a uniform wall thickness as well as high surface quality with the fewest wrinkles.The results obtained from the surface morphological FE model considering material inhomogeneity and surface morphology of the composites are the closest to the experimental results compared to the basic and Voronoi FE model.During MDD process,the drawing forces decrease with increasing annealing temperature as a consequence of the strength reduction.
基金Projects(51135009,51105371) supported by the National Natural Science Foundation of China
文摘LuGre model has been widely used in friction modeling and compensation.However,the new friction regime,named prestiction regime,cannot be accurately characterized by LuGre model in the latest research.With the extensive experimental observations of friction behaviors in the prestiction,some variables were abstracted to depict the rules in the prestiction regime.Based upon the knowledge of friction modeling,a novel friction model including the presliding regime,the gross sliding regime and the prestiction regime was then presented to overcome the shortcomings of the LuGre model.The reason that LuGre model cannot estimate the prestiction friction was analyzed in theory.Feasibility analysis of the proposed model in modeling the prestiction friction was also addressed.A parameter identification method for the proposed model based on multilevel coordinate search algorithm was presented.The proposed friction compensation strategy was composed of a nonlinear friction observer and a feedforward mechanism.The friction observer was designed to estimate the friction force in the presliding and the gross sliding regimes.And the friction force was estimated based on the model in the prestiction regime.The comparative trajectory tracking experiments were conducted on a simulator of inertially stabilization platforms among three control schemes:the single proportional–derivative(PD)control,the PD with LuGre model-based compensation and the PD with compensator based on the presented model.The experimental results reveal that the control scheme based on the proposed model has the best tracking performance.It reduces the peak-to-peak value(PPV)of tracking error to 0.2 mrad,which is improved almost 50%compared with the PD with LuGre model-based compensation.Compared to the single PD control,it reduces the PPV of error by 66.7%.
基金the support from the National Key Research and Development Program of China[2018YFA0703400].
文摘The infrared conformal window is one of the most critical components in aircraft.Conformal windows with high performance bring low aberrations,high aerodynamic performance,reliability in extreme working environments,and added value for aircraft.Through the past decades,remarkable advances have been achieved in manufacturing technologies for conformal windows,where the machining accuracy approaches the nanometer level,and the surface form becomes more complex.These advances are critical to aircraft development,and these manufacturing technologies also have significant reference values for other directions of the ultra-precision machining field.In this review,the infrared materials suitable for manufacturing conformal windows are introduced and compared with insights into their performances.The remarkable advances and concrete work accomplished by researchers are reviewed.The challenges in manufacturing conformal windows that should be faced in the future are discussed.
基金the National Natural Science Foundation of China(Grant No.61973033)Preliminary Research of Equipment(Grant No.9090102010305)for funding the experiments。
文摘The longitudinal dispersion of the projectile in shooting tests of two-dimensional trajectory corrections fused with fixed canards is extremely large that it sometimes exceeds the correction ability of the correction fuse actuator.The impact point easily deviates from the target,and thus the correction result cannot be readily evaluated.However,the cost of shooting tests is considerably high to conduct many tests for data collection.To address this issue,this study proposes an aiming method for shooting tests based on small sample size.The proposed method uses the Bootstrap method to expand the test data;repeatedly iterates and corrects the position of the simulated theoretical impact points through an improved compatibility test method;and dynamically adjusts the weight of the prior distribution of simulation results based on Kullback-Leibler divergence,which to some extent avoids the real data being"submerged"by the simulation data and achieves the fusion Bayesian estimation of the dispersion center.The experimental results show that when the simulation accuracy is sufficiently high,the proposed method yields a smaller mean-square deviation in estimating the dispersion center and higher shooting accuracy than those of the three comparison methods,which is more conducive to reflecting the effect of the control algorithm and facilitating test personnel to iterate their proposed structures and algorithms.;in addition,this study provides a knowledge base for further comprehensive studies in the future.
基金National Natural Science Foundation of China(61973037)National 173 Program Project(2019-JCJQ-ZD-324).
文摘To solve the problem of the low interference success rate of air defense missile radio fuzes due to the unified interference form of the traditional fuze interference system,an interference decision method based Q-learning algorithm is proposed.First,dividing the distance between the missile and the target into multiple states to increase the quantity of state spaces.Second,a multidimensional motion space is utilized,and the search range of which changes with the distance of the projectile,to select parameters and minimize the amount of ineffective interference parameters.The interference effect is determined by detecting whether the fuze signal disappears.Finally,a weighted reward function is used to determine the reward value based on the range state,output power,and parameter quantity information of the interference form.The effectiveness of the proposed method in selecting the range of motion space parameters and designing the discrimination degree of the reward function has been verified through offline experiments involving full-range missile rendezvous.The optimal interference form for each distance state has been obtained.Compared with the single-interference decision method,the proposed decision method can effectively improve the success rate of interference.
基金National Natural Science Foundation of China(Grant No.22005275)to provide fund for conducting experiments.
文摘In order to improve the energy output consistency of 3, 3’-diamino-4, 4’-azoxyfurazan(DAAF) in the new insensitive booster and the safety and efficiency in the preparation process, a continuous preparation system of DAAF from synthesis to spherical coating was designed and established in this paper, which combined ultrasonic micromixing reaction with microdroplet globular template. In the rapid micromixing stage, the microfluidic mixing technology with ultrasonic was used to synergistically strengthen the uniform and rapid mass transfer mixing reaction between raw materials to ensure the uniformity of DAAF particle nucleation-growth, and to prepare high-quality DAAF crystals with uniform structure and morphology and concentrated particle size distribution. In the microdroplet globular template stage, the microfluidic droplet technology was used to form a droplet globular template with uniform size under the shear action of the continuous phase of the dispersed phase solution containing DAAF particles and binder. The size of the droplet template was controlled by adjusting the flow rate ratio between the continuous phase and the dispersed phase. In the droplet globular template, with the diffusion of the solvent in the dispersed phase droplets, the binder precipitates to coat the DAAF into a ball, forming a DAAF microsphere with high sphericity, narrow particle size distribution and good monodispersity. The problem of discontinuity and DAAF particle suspension in the process was solved, and the coating theory under this process was studied. DAAF was coated with different binder formulations of fluororubber(F2604), nitrocellulose(NC) and NC/glycidyl azide polymer(GAP), and the process verification and evaluation of the system were carried out. The balling effects of large, medium and small droplet templates under different binder formulations were studied. The scanning electron microscope(SEM) results show that the three droplet templates under the three binder formulations exhibit good balling effect and narrow particle size distribution. The DAAF microspheres were characterized by powder X-ray diffraction(XRD), differential scanning calorimetry(DSC), thermo-gravimetric(TG) and sensitivity analyzer. The results showed that the crystal structure of DAAF did not change during the process, and the prepared DAAF microspheres had lower decomposition temperature and lower mechanical sensitivity than raw DAAF. The results of detonation parameters show that the coating of DAAF by using the above three binder formulations will not greatly reduce the energy output of DAAF, and has comparable detonation performance to raw DAAF. This study proves an efficient and safe continuous system from synthesis to spherical coating modification of explosives, which provides a new way for the continuous, safe and efficient preparation of spherical explosives.
基金National Natural Science Foundation of China under Grant No.61973037China Postdoctoral Science Foundation 2022M720419 to provide fund for conducting experiments。
文摘The identification of intercepted radio fuze modulation types is a prerequisite for decision-making in interference systems.However,the electromagnetic environment of modern battlefields is complex,and the signal-to-noise ratio(SNR)of such environments is usually low,which makes it difficult to implement accurate recognition of radio fuzes.To solve the above problem,a radio fuze automatic modulation recognition(AMR)method for low-SNR environments is proposed.First,an adaptive denoising algorithm based on data rearrangement and the two-dimensional(2D)fast Fourier transform(FFT)(DR2D)is used to reduce the noise of the intercepted radio fuze intermediate frequency(IF)signal.Then,the textural features of the denoised IF signal rearranged data matrix are extracted from the statistical indicator vectors of gray-level cooccurrence matrices(GLCMs),and support vector machines(SVMs)are used for classification.The DR2D-based adaptive denoising algorithm achieves an average correlation coefficient of more than 0.76 for ten fuze types under SNRs of-10 d B and above,which is higher than that of other typical algorithms.The trained SVM classification model achieves an average recognition accuracy of more than 96%on seven modulation types and recognition accuracies of more than 94%on each modulation type under SNRs of-12 d B and above,which represents a good AMR performance of radio fuzes under low SNRs.
基金National Natural Science Foundation of China(61973037)National 173 Program Project(2019-JCJQ-ZD-324)。
文摘Uniform linear array(ULA)radars are widely used in the collision-avoidance radar systems of small unmanned aerial vehicles(UAVs).In practice,a ULA's multi-target direction of arrival(DOA)estimation performance suffers from significant performance degradation owing to the limited number of physical elements.To improve the underdetermined DOA estimation performance of a ULA radar mounted on a small UAV platform,we propose a nonuniform linear motion sampling underdetermined DOA estimation method.Using the motion of the UAV platform,the echo signal is sampled at different positions.Then,according to the concept of difference co-array,a virtual ULA with multiple array elements and a large aperture is synthesized to increase the degrees of freedom(DOFs).Through position analysis of the original and motion arrays,we propose a nonuniform linear motion sampling method based on ULA for determining the optimal DOFs.Under the condition of no increase in the aperture of the physical array,the proposed method obtains a high DOF with fewer sampling runs and greatly improves the underdetermined DOA estimation performance of ULA.The results of numerical simulations conducted herein verify the superior performance of the proposed method.
