With the rising of energy requirements, Lithium-Ion Battery (LIB) have been widely used in various fields. To meet the requirement of stable operation of the energy-storage devices in extreme climate areas, LIB needs to further expand their working temperature range. In this paper, we comprehensively summarize the recent research progress of LIB at low temperature from the perspectives of material and the structural design of battery. First, the fundamental reasons of limiting low-temperature performance of LIB are analyzed. Then, the rational strategies for improving the low-temperature performance of LIB are discussed from four aspects: the research and optimization of electrolyte, the modification and exploitation of electrode materials, the development of new types of battery system as well as the design of Battery Thermal Management System (BTMS). Finally, the urgent problems to be solved in low-temperature LIB research are summarized, and the feasible research direction is suggested for the development of a new generation of low-temperature LIB.

Aimed at the conservative problem of integrity risk and continuity risk allocation in the traditional Advanced Receiver Autonomous Integrity Monitoring (ARAIM) algorithm, a new integrity risk and continuity risk allocation method based on Particle Swarm Optimization (PSO) algorithm is proposed. This method uses different allocation strategies as different particles in the algorithm, and selects the weighted sum of the vertical protection levels corresponding to different fault subsets as the fitness function. Each particle updates its position and speed based on the principle of particle swarm optimization until the conditions are met, and then the optimized allocation strategy and the corresponding vertical protection level are obtained. The algorithm is verified through dual constellations and compared with traditional methods. The results show that the integrity risk and continuity risk allocation strategy based on the particle swarm optimization algorithm optimizes the vertical protection level and improves the ARAIM global availability.

Aircraft test can simulate the flight environment to verify whether the aircraft functions meet the requirements and the performance is accurate. In recent years, the aircraft assembly process has gradually turned into three-dimensional design, while aircraft test is still limited to the description of test tasks and process execution in the form of documents. Based on the Model Based Definition (MBD), the top-level design of aircraft test is studied, and the concept of test process design and the digital definition method of test process model are proposed. The whole process of aircraft test is divided into four stages, completing process model definition from test design to test results and achieving partial engineering verification. The results show that the MBD-based digital definition result can be used as the only data source to realize the unified expression and information transmission of aircraft test.

In order to study the effect of deposition of pollutants on film cooling of blade leading edge of turbine, the experiment used paraffin deposition to simulate real deposits.By changing the mainstream temperature, the angle of film hole jet and the diameter of film hole, the variation of film cooling efficiency and deposition rate in deposition environment was observed experimentally. The experimental results show that the morphology of particulate deposition on the barrier surface is significantly affected by the mainstream temperature. When the mainstream temperature approaches the melting point of particulate matter, the deposition coverage is most obvious. Under the same experimental conditions, with the increase of jet angle, the coverage area of single film hole decreases, and the film cooling efficiency decreases. Before and after deposition, the maximum difference between film cooling efficiency at jet angle 25° and jet angle 65° is 2% and 5.6%, and deposition rate increases with the increase of jet angle; with the increase of pore diameter, the film cooling efficiency first decreases and then increases. Whether there is deposition or not, the film cooling efficiency of 4.5 mm pore diameter is the highest, 3.6% and 3.2% higher than that of 3 mm pore diameter. The deposition rate is the lowest when the pore diameter is 3 mm.

Electronic information equipment will emit electromagnetic wave unintentionally, which contains useful information. It will lead to the electromagnetic information leakage, thus threatening the information security. The traditional electromagnetic information leakage detection methods are difficult to extract useful information from uncertain electromagnetic leakage signals in complex environments. Aimed at the problem of electromagnetic information security, the electromagnetic information leakage detection is studied. A detection method based on deep learning is proposed. The method designs a one-dimensional convolutional neural network suitable for electromagnetic signals, and combines an improved gradient-weighted class activation mapping algorithm. It can locate and extract the electromagnetic leakage information characteristics intelligently under the condition of unknown the characteristics through deep learning so as to solve the problem of extracting electromagnetic leakage information in complex environments. The effectiveness of the proposed method is verified by experiments and simulation.

The online measurement system of gas pressure, flow and other parameters was established to realize the regulation and control of the measurement and control system through the data acquisition system of industrial personal computer, combined with sensor technology, signal processing technology, etc. The pressure and flow rate of the flexible gripper under different initial pressures during contraction and expansion were collected respectively, then the pressure flow diagram of the flexible gripper was drawn by SigmaPlot, and the flow pressure output characteristics of the flexible gripper were analyzed. Finally, the pneumatic power was calculated to study the energy consumption law. The results show that through the contraction experiment of the flexible gripper, the difference between the given initial pressure and the pressure generated by the flexible gripper is small, and the loss of pneumatic power is relatively small. In the expansion experiment of the flexible gripper, because the initial pressure provided is indirectly acting on the flexible gripper through the vacuum generator, the difference between the pressure provided and the pressure generated by the flexible gripper is big. Larger initial pressure needs to be provided in order to make the flexible gripper reach the specified pressure. The pneumatic power loss of flexible gripper is lower during contraction than during expansion.

In order to solve the problem of frequent updating of information between UAVs and control input in multi-UAV formation target tracking, this paper proposes a multi-UAV formation target tracking control algorithm based on event-triggered mechanism. Firstly, a new integrated method of formation description and target tracking with event-triggered strategy is presented, which simplifies the complexity of algorithm design and makes the working process of triggered mechanism more intuitive. Secondly, distributed target tracking control law is designed, and event-triggered function is designed only based on estimated state value, so that the problem of updating communication and control input between UAVs is transformed into the problem of determining the value of triggered function. At the same time, the minimum triggered interval coefficient is designed to avoid the possible "Zeno behavior". Finally, the algorithm is verified by simulation with different formation motion modes. The results show that the proposed algorithm can make UAV formation track the target when the number of inter-aircraft communication and control update is significantly reduced.

The information exchange, in the forms of pictures, voice, video and other multimedia, plays an important role in network communication, as well as many illegal information disseminations are hidden. Steganalysis is an effective way of detecting secret information. This paper proposes a universal HEVC video steganalysis algorithm based on multi-scale residual convolution network, mainly consisting of residual calculation, feature extraction and binary classification. In the feature extraction part, residual convolution layer, multi-scale residual convolution module and a steganalysis residual block are proposed. Our experimental results show that the detection rate of this method based on video pixel domain analysis network is as high as 99.75%, which has greater advantages than the traditional manual feature extraction methods.

To handle the precise trajectory control problem of the cable towed vehicle under unknown airflow disturbances, the minimal learning parameter neural network estimator based dynamic surface trajectory control method is proposed for the towed vehicle. Firstly, combined with the multi-body dynamic model of the cable towed system, the towed vehicle's six-degree-of-freedom nonlinear model is established and then formulated in the affine nonlinear form. Secondly, considering the comprehensive influence on the towed vehicle by the unknown airflow disturbances (such as the trailing vortex, atmospheric turbulence, gust, etc.) and the variably unmeasurable cable tensions, the minimal learning parameter neural network based state/disturbance online estimators are established to accurately reconstitute the unmeasurable lumped disturbance of system. Thirdly, on the basis of the above state/disturbance online estimators, the minimal learning parameter neural network state/disturbance estimator based dynamic surface trajectory control method is proposed. Finally, the simulation results show that the proposed method can achieve the towed vehicle's trajectory stabilization and maneuvering trajectory tracking control.

Bolted joints are the weak points of composite structures. Therefore, the design of bolted joints is one of crucial issues in the design of composite structure. In this paper, a probability analysis model for the failure load of a Carbon Fiber Reinforced Polymer (CFRP) composite bolted joint was built by combining the modified characteristic curve method and the statistical model of random parameters. The key influence parameters were regarded as the design variables, the reliability index was considered as the constraint, and the mass of the joint was the design goal. Accordingly, a reliability-based design optimization method was developed for the CFRP bolted joint. The orthogonal test design method was used to establish the reliability-based optimal design calculation scheme. The optimization results show that, when the key influence parameters X_C is 2 450 MPa, t_ply is 0.174 mm, and E₁₁ is 225 GPa, the best design of the joint is obtained. According to this scheme, when the external load is 17.5 kN, the reliability of the joint is increased from 0.998 to above 0.999 999, and the mass of the joint is reduced by 6.44%.

Aimed at the design and maintenance of long-duration repeat ground-track orbit, this paper deals with a semi-analytical method based on high-order Poincaré maps for the optimal design and control of repeat ground-track orbit in the high-precision gravity fields, including the factors of atmospheric drag, solar radiation pressure and three-body perturbations. The method is based on the high-order expansion of Poincaré maps, which is expressed as the polynomials, to propagate the orbit for one or more repeat cycles, enabling the precise orbit design and control by performing impulsive control at the equatorial crossings. The method, aimed at both the high-accuracy and low-accuracy constraints, is proposed and applied to missions like the repeat pattern of TerraSAR-X, Landsat-8, IRS-P6, SPOT-7 and UoSAT-12. The present method has the advantages in high computational efficiency and high accuracy, which is suitable for the on-board autonomous orbital propagation and orbital control.

Time-Triggered Ethernet (TTE) makes communication tasks have strict determinacy and conflict free by global time-triggered mechanism, which is suitable for mixed critical application fields such as avionics. TTE network provides three different traffic types: Time-Triggered (TT) traffic with low jitter and bounded end-to-end delay, Rate Constrained (RC) traffic with limited end-to-end delay, and no real-time guaranteed "Best Effort" (BE) traffic. Aiming at the problem that Satisfiability Modulo Theories (SMT) and other methods do not consider the influence of TT traffic routing and scheduling on RC traffic delay in the process of generating the TT traffic scheduling timetable, in order to optimize the real-time performance of TTE network, this paper proposes a scheduling algorithm based on greedy randomized adaptive search procedure. The Worst-Case end-to-end Delay (WCD) of RC traffic is considered in the generation process of TT traffic offline scheduling timetable. Under the premise of ensuring the schedulability of TT traffic, the WCD of RC traffic is reduced by routing strategy and scheduling strategy. The comparative experimental results show that the proposed method can effectively improve the real-time performance of the network. Through the comparative analysis of A380 topology networking cases, the average delay of RC traffic is reduced by 14.34%. Also, the larger the network traffic scale, the greater the income of this method.

In order to solve the problem that the state changes of only one variable instead of related variables are considered in the process of aircraft engine condition prediction, an online prediction model of the state of engine based on multivariate Kernel Extreme Learning Machine (KELM) is proposed. First, the phase space reconstruction of multivariable time series is used to transform the temporal correlation into the spatial correlation. Then, by studying the relationship between KELM and the Kernel Recursive Least Squares (KRLS), KRLS is extended into the online sparse KELM framework. Finally, the samples are made sparse by using approximate linear dependence to control the growth of network structure, and ultimately online prediction of multivariable nonstationary series is realized. The prediction results of engine flight parameters of a certain trainer show that, compared with KB-IELM, NOS-KELM and FF-OSKELM in the premise of online prediction, the prediction accuracy is decreased by 90.61%, 58.14% and 25.77% respectively, and the prediction stability is decreased by 99.61%, 75.03% and 28.59% respectively, with higher prediction accuracy and stability. All methods get best results with multivariate inputs, which also proves thatthe consideration of multivariable state factors is of great significance to the online prediction of single variable as well.

This paper proposes a multi-source model extraction method based on electromagnetic interference element theory to solve the modeling problem of digital circuit electromagnetic conducted emission. Based on the basic emission waveform theory, this paper divides the digital circuit electromagnetic conducted emission model into two parts: basic elements and extended elements. In view of the characteristics of digital circuit clock signals, the trapezoidal pulse sequence is selected as the basic element form, and an improved joint estimation algorithm is proposed to extract the basic element parameters and the corresponding extended element system transfer function model. Aimed at the coexistence of multiple sources of digital circuits, a multi-source identification and separation method based on autocorrelation function is proposed to separate different basic elements from a set of test data, and finally complete the modeling of electromagnetic conducted emission of digital circuits. The simulation and experimental results verify the feasibility and accuracy of the proposed method.

The Pilot Induced Oscillations (PIO) pose a serious threat to the flight safety of aircraft. Predicting the PIO of full-size aircraft preliminarily based on flight test of dynamically similar scaled model helps to reduce the test risks and save cost. Bandwidth criterion and Neal-Smith criterion are selected as the evaluation criteria for the longitudinal Category Ⅰ PIO caused by the time delay from control stick operation to control command generation. The similar proportional relations of the PIO characteristic parameters between full-size aircraft and scaled model are analyzed first, and then a method to predict longitudinal Category Ⅰ PIO of the full-size aircraft based on scaled model is established. Finally, a military transport aircraft and its scaled model are taken as the sample aircraft of simulation verification. The results show that the similar proportional relations obtained by analysis are correct, and the prediction of Category Ⅰ PIO of full-size aircraft is accurate based on scaled model test data.

The aerodynamic coupling effect of the composite flight of aircraft via wingtip-jointed structure determines the dynamic characteristics different from those of its independent flight, where safety risks might exist. In order to investigate the dynamic characteristics of the wingtip-jointed composite aircraft, the Newton-Euler method and Robberson-Wittenburg method are used to derive the 7-degree-of-freedom nonlinear dynamics and kinematics equations of the multi-body system of the wingtip-jointed composite aircraft composed of two aircraft. Under the aerodynamic quasi-steady assumption, uncoupling aerodynamic force formula for two-aircraft composite system is established, and the composite aircraft system's three-dimensional modeling and unstructured meshing are further carried out based on the CFD method to obtain the aerodynamic data. The dynamic simulation platform is built, and the dynamic simulations under the quasi-trimming strategy and the full-trimming strategy are carried out on the dynamic simulation platform. The result proves that the aircraft cannot continue to fly stably under the quasi-trimming strategy, while the motion parameters of the composite system under the full-trimming strategy always tend to be stable. Under the full-trimming strategy, the decoupling linearization method using small disturbance hypothesis is used to rearrange the terms of the 7-degree-of-freedom dynamic equations, and study the two new divergent eigenvectors in the eigenvalues of the composite system motion modes, which shows that the two divergent modes are dominated by the relative roll angle and angular velocity. Meanwhile, the characteristics of other modes compared with the single-plane flight are summarized and analyzed.

The ejection emergency flight data recording and tracking system consists of the intelligent ejection separation, tow-type image tracking, inflatable soft-landing and data transmitting. In this paper, the key subsystem design and UAV test verification are carried out. According to the characteristics of the parachute-airbag module, the variation of the canopy drag coefficient in the airbag wake region is analyzed. The results show that the radius of the airbag and the nominal diameter of the canopy are the main factors affecting the canopy drag coefficient. The canopy drag coefficient decreases with the increase of the radius of airbag, and increases with the increase of the nominal diameter of the canopy. Based on the aerodynamic analysis and the numerical simulation, the canopy drag coefficient formula is obtained. Meanwhile, the full functions are achieved by UAV test, and it is proved that the system scheme is reasonable and feasible. It provides an important reference for the subsequent engineering application.

The smooth time-varying constraint is a mechanical effect of continuous contact produced by the rubbing between rotor and stator, in which the periodic time-varying constraint is applied to the rotor. The additional stiffness curve caused by contact between the stator and the rotor is a smooth and derivable function with time. A smooth time-varying constraint model is established based on the orbit of rotor in experiment, and the modal frequency, stability and response of rotor system with smooth time-varying constraint are analyzed based on the Hill method, which provides an analysis frame for the fault identification and stability analysis of the rubbing rotor. The research results show that the rotor with smooth time-varying constraint has the characteristics of frequency coupling, multi-frequency and instability. In the unstable speed region, the amplitude of the rotor gradually increases with time. The frequency component that causes the instability of the rotor system is the frequency component whose real part of eigenvalue is greater than 0 in the rotor modal analysis. In the stable speed region, the rotor's frequency response is mainly the frequency combination composed of speed frequency and contact frequency.

The efficient and orderly swarms control mode is the prerequisite for the swarms to successfully complete the combat mission. Aimed at the problem of UAV swarms control, a hybrid swarms control based on Agent and cellular automata is proposed by combining the centralized and distributed control modes. Based on the analysis of UAV swarms operation flow, the framework of UAV swarms control system, communication topology and swarms control rules are constructed. The swarms' individuals are divided from top to bottom into three levels: center leader, group leader, and individual UAV. The upper level adopts top-down centralized control to the lower level, and the same level adopts bottom-up distributed control. On this basis, using the hierarchy of Agent model and the homogeneity of cellular automata model, a swarms hybrid control model based on Agent and cellular automata is designed to realize the effective combination of the two control modes. The cellular automata model realizes the basic swarms rules of aggregation, separation and uniform speed, and the Agent model realizes the cooperative interaction rules among individuals at different levels. Under the background of formation assembly and maintenance task, three kinds of control: distributed, centralized and hybrid, are compared and simulated. The simulation results show that the swarms based on hybrid control have obvious advantages in formation controllability, following, consistency and reducing communication load, which verifies the effectiveness of the hybrid swarms control method.

Accurately predicting the intercept point and intercept time of the interceptor in real time is an effective way to realize the mid-course penetration of ballistic missiles. In order to predict the intercept point coordinates and intercept time during the mid-course penetration process of ballistic missile, an online prediction method based on supervised learning is proposed in this paper. Using the shutdown parameters and the shutdown time of the boost stage of the interceptor as inputs, the prediction model of intercept time and intercept point was established. Based on the multi-layer perceptron neural network, a supervised learning algorithm was formulated, and the interceptor's parameters were obtained through the attack and defense simulation to make the set of training data. The network training was completed offline. The simulation results show that the neural network can effectively predict the interception time and the coordinates of interception point online, and the relative error of the prediction results is 0.124 3% and 0.128 5% respectively; the average error of the prediction results of intercept time is 0.224 0 s; the average distance error of the prediction results of intercept point is 2 016.48 m. They all meet the accuracy requirements.

The steady-state experiment and numerical simulation were carried out to investigate the flow structure and heat transfer characteristics in the rotating cavity with axial flow. By changing the axial flow coefficient, rotating Reynolds number, etc., the radial distribution of temperature and Nusselt number on both sides of the disk and the inner side of the disk cone under different working conditions was explored. The results show that: the radial distribution of temperature on both sides of the disk is concave, and the heat transfer intensity on the upwind side of the disk is generally higher than that on the leeward side. The cone disk conducts heat conduction to the disks on both ends, and the radial distribution of the wall surface temperature is high in the middle and low on both sides. With the increase of the axial flow coefficient, the gas convection inside the disk cavity was intensified, the radial arm and vortex pair became explicit, and the heat transfer effect on the surface of the rotating disk and the cone disk was enhanced. The flow heat transfer characteristics in the cavity of the rotating disk are influenced by forced convection and Rayleigh-Benard like convection.

According to the multi-field coupling characteristics of air-cooled turbine blades, numerical simulation of high-pressure turbine guide vanes with different air-cooling structures is carried out by the flow-heat coupling method. In internal cooling turbine blade example, by comparing the experimental data to select a higher-accuracy Conjugate Heat Transfer (CHT) calculation scheme, the multi-field characteristics and coupling mechanism of the internal cooling guide vane are analyzed. On this basis, the turbine guide vanes with film cooling holes and internal cooling channels are the research object, the interaction between cooling jet and main stream are focused on, and the fluid thermal coupling relationship in near wall boundary layer and related questions such as the factors affecting the air cooling efficiency are discussed. The results show that the use of flow-heat coupling calculation method and a suitable turbulent transition model is conducive to improving the simulation accuracy. Flow field and temperature field of the air-cooled guide vane are closely coupled, and the flow heat-transfer characteristics affect each other. In case of low speed rate, increased cool air flow can improve the cooling efficiency of the film, and if the flow of cold air is increased to a certain value, the increase in the cold flow will cause a poor upstream cooling effect behind the air-cooled hole and a better downstream cooling effect. High-speed cooling interacts with main stream, which will produce complex flow structures such as kidney-shaped vortices and horseshoe vortices that have certain influences on temperature distribution.

Aimed at reducing the overall misrecognition cost of ballistic targets, A One-Dimensional Convolutional Neural Network (1D-CNN) based on Cost-Sensitively Pruning (CSP) is proposed for ballistic target high-resolution range profile recognition. Firstly, based on the lottery ticket hypothesis, a unified framework is proposed to reduce the model complexity and overall misidentification cost concurrently. On this basis, a gradient-free optimization method of network structure based on artificial bee colony algorithm is proposed, which can automatically find the cost-sensitive subnetwork of 1D-CNN, namely, cost-sensitively pruning. Finally, in order to make the cost-sensitive sub-network still be aimed at minimizing the cost of misrecognition during the fine-tuning process, a novel Cost-Sensitive Cross Entropy (CSCE) loss function is proposed to optimize the training, so that the cost-sensitive sub-network focuses more on correctly classifying the categories with higher misrecognition cost to further reduce the overall misrecognition cost. The experimental results show that the proposed 1D-CNN combined with the CSP and CSCE loss function has a lower overall misrecognition cost than traditional 1D-CNN under the premise of maintaining a higher recognition accuracy, and reduces the computational complexity by more than 50% as well.

Aimed at the fatigue performance of aluminum alloy plate with hybrid adhesive-rivet single-sided patch, specimens with four different methods including un-repair, riveted repair, adhesive repair and adhesive-rivet repair were designed and subjected to fatigue tests. The finite element models of specimens were established, and the structural stress distributions and the crack length-crack tip Stress Intensity Factor (SIF) curves were obtained and compared with the test results. The results show that adhesive repair and adhesive-rivet repair methods can effectively reduce the stress level at the crack and the crack growth rate. Compared with un-repair specimens, the fatigue life of adhesive repair and adhesive-rivet repair methods is increased by 184.3% and 197.3%, respectively. For the adhesive-rivet repair, the rivets can inhibit the debonding of the adhesive layer, and the repair quality of this method is more reliable and effective than that of the adhesive repair method. The Finite Element Analysis (FEA) results are in good agreement with the test results, and the SIF error of FEA is approximately within 8%.