The output torque of the motor direct-driven servo system acts directly on the load, due to chip process defects, phase inductance, detection circuit asymmetry and other factors, motor stator slotting and other factors, the first and second harmonics of phase current and tooth harmonic will directly affect the stability of electromagnetic torque. The first step in enhancing the system’s low-speed smoothness is identifying the root causes of the three different kinds of low-frequency harmonics. Second, in order to enhance the harmonic suppression capability in cases when the magnetic circuit is not ideal, a unique electrical angle update and mechanical angle assignment algorithm for center current (CC-EUMA) is presented for the first harmonic.For the second harmonic and tooth harmonic, the double quasi-proportional resonant control algorithm for speed loop (SL-DQPR) is proposed, which has the advantages of both strong anti-disturbance ability and low tuning difficulties while filtering harmonics. Finally, the effectiveness of the two algorithms is verified by simulation and experiment. After adding these algorithms, the tracking error of the motor in no-load operation is reduced to one-third of the original, which realizes the smooth operation of the system with limited hardware resource overhead and provides a new idea for the low-speed control of the space direct drive servo system. The tracking error of the motor in no-load operation is reduced to one-third of its original value once these algorithms are included, allowing the system to operate smoothly with less hardware resource overhead and offering a fresh concept for the low-speed management of space direct drive servo system.

Trajectory data is valuable for a variety of applications. However, it has been a long-standing challenge to share and utilize trajectory data while protecting users’ privacy. Currently, the prevailing shared trajectory privacy-preserving methods are to generate complete synthetic trajectories that are highly similar to real trajectories based on differential privacy, which results in poor utility of synthesis trajectories and is vulnerable to location privacy inference attacks. To address these problems, this paper proposed a utility-enhanced synthesis method of differentially private trajectories (UtiE-DPT). By dividing the real trajectory dataset spatially, this method constructed a fine-grained adaptive density grid structure to discretize the real trajectory and designed a Markov transition matrix, trajectory travel distribution, and trajectory length distribution calculation model suitable for the adaptive density grid structure, so as to extract key statistical features to maintain the utility of real trajectories and thus enhance the utility of synthetic trajectories. To preserve the users’ privacy, the differential privacy technique was employed to perturb these key statistical features. Finally, a synthetic trajectory against inference attacks was generated according to the extracted features and anti-attack constraint strategy. Comprehensive experiments on real datasets and simulation datasets show that compared with the existing trajectory synthesis privacy protection methods such as DP-Star and AdaTrace, the UtiE-DPT not only protects trajectory privacy and resists location privacy inference attacks but also improves the utility of synthetic trajectories. Without considering the inference attacks, the query error of UtiE-DPT for generating synthetic trajectories is 21%–27% lower than AdaTrace and 32%–53% lower than DP-Star. After resisting the inference attacks, although the robustness of the synthetic trajectory is reduced by about 1%–2% compared with AdaTrace, the query error is reduced by 16%–21% compared with AdaTrace, achieving a better balance between privacy protection and utility.

When a haze-degraded scene is under uneven lighting conditions, some scene details will be less visible due to hazy obscuration and light shadows. To address this issue, a hazy image restoration algorithm with double light curtain boundary constraints based on an improved atmospheric scattering model was proposed. The imaging principle of the conventional atmospheric scattering model was analyzed, and the model was improved by using its degradation mechanism combined with the Retinex theory. The mean inequality relation and Gaussian decay function were introduced to estimate the eigenvalue of the atmospheric light curtain. In addition, the upper and lower boundaries were set to constrain the estimated values. The scene-incident light was obtained by an improved atmospheric scattering model, which was compensated by using the bright channel of the hazy image through the bright channel prior method. The method of local atmospheric light acquisition was improved. A mid-channel-based local atmospheric light estimation method was proposed. The estimated atmospheric light curtain and scene-incident light were introduced into an improved atmospheric scattering model to obtain a hazy-free image. Then, the hazy-free image was fused with the image texture layer to obtain the final restored image. According to the subjective and objective analyses of the experimental results, the proposed algorithm can not only effectively restore the hazy images with uneven scene illumination but also get a better restoration effect for the haze scenes. The restored scene is clear, and the brightness is moderate.

In order to optimize the service process of the integrated transportation hub, the dynamic characteristics of the aggregation behavior of arriving passengers were analyzed. The transition mechanism of arriving passenger aggregation behavior between inverse gamma distribution, gamma distribution, and chi-square distribution was studied. It revealed that this aggregation behavior was affected by the flight operation time and transfer mode utility, which was converted into the time value and utility value of arriving passengers, respectively. On this basis, a dynamic model of arriving passengers driven by the dual values was established based on these three distributions, and the output was the distribution of arriving passengers with adjustable parameters. The results show that the simulation output with adjustable parameters is consistent with the real distribution, which provides a method and basis for accurate prediction of the distribution situation of arriving passengers at the airport.

A risk assessment model with quantitative uncertainty features is suggested in order to assess air freight forwarders’ violations on air cargo transportation in an efficient manner. The Bayesian network model is constructed based on the threat possibility, security vulnerability and consequence severity of violations of air freight forwarders. The average difference of experts, the lack of expert knowledge base and the polarization of expert evaluation are used to quantify the uncertainty of risk assessment results of air freight forwarders’ violations. Combined with the application example of Shenzhen Bao’an International Airport, this paper analyzes the risks and uncertainties of risk assessment results of air freight forwarders’ violations. The study’s findings demonstrate that the risk assessment’s conclusions are consistent with the real state of air cargo, and the air freight forwarders’ priority order of violations, which is established based on the risk level and uncertainty indices, offers airlines and airports a new avenue for methodically preventing risks.

The wavefront distortion caused by the passage of radar echoes through the atmosphere, the external flow field of the aircraft, and the radome has a crucial influence on the angle measurement error of active radar single-pulse. The impact of the refractive index gradient caused by the turbulent structure on the wavefront distortion and the numerical solution accuracy of the weak form of the wave equation were analyzed. The “explicit” gradient term correction approach and the “gradient reconstruction” method of supplementing the small-scale structure of the density field with the turbulent vortex model for the weak form of the electromagnetic wave equation were proposed. Computer numerical simulation was conducted using the finite element method. The simulation results indicate that one of the significant causes of the radar angle measurement error is the electric field distortion induced by small-scale turbulence, and as the scale of the vortex structure decreases and the wavelength lengthens, the electric field distortion intensifies, and the angle measurement error increases.

This study introduces the text summarizing model SPOATS, which is driven by fact triples, to solve the issue that the current abstractive text summarization models do not entirely exploit the factual information of text in decoding. The model is based on a Transformer structure, which contains a double encoder capable of extracting facts and a decoder for combining factual features. To begin, the LTP-BiLSTM-GAT (LBiG) model is built and paired with the optimal factual triple selection technique suggested in this paper. The optimal factual triples are then extracted from the unstructured Chinese text to acquire the feature encoding of factual information. Then, the improved S-BERT model is used to represent the original text at the sentence-level vector to obtain the semantic rich sentence encoding. Finally, an attention-based fact fusion mechanism is designed to fuse the dual-encoding features, which can improve the ability of the model to select factual information in the decoding stage. The experimental results show that the proposed model has improved the value of ERPG by 2.0% compared to the baseline model on the dataset LCSTS, and the summary quality has been significantly improved.

In view of the high nonlinearity of pneumatic artificial muscle and the difficulty in establishing a hysteresis model, the hysteresis characteristics of pneumatic artificial muscle were studied, and an improved Maxwell model based on slip operator was proposed. First of all, the contraction force test platform of pneumatic artificial muscle was set,on which the static force experiment and dynamic force experiment were carried out. The hysteresis force curve of the pneumatic artificial muscle was obtained, and the effects of different strokes, different inflation pressures, and different expansion rates on the hysteresis loop were considered respectively.The hysteresis characteristics of the pneumatic artificial muscle were obtained. Then, since the traditional Maxwell model could not represent the asymmetrical hysteresis characteristics of pneumatic artificial muscle very well, the hysteresis curves were contracted from the upper and lower parts, respectively, and the obtained operators could represent the non-local memory and asymmetry of the contraction curves of the pneumatic artificial muscle better. The maximum error was controlled within 6.8%, andthe error of the middle section was controlled within 2.0%, matching the experimental curve well and verifyingthe universality of the model.

In order to solve the problem of low fault diagnosis accuracy caused by complex operating conditions and insufficient samples of rolling bearings, a fault diagnosis method based on the Markov transition field (MTF) and the stripe pooling convolutional neural network (SPCNN) for small sample rolling bearings under variable working conditions was proposed. Firstly, one-dimensional bearing signals were transformed into two-dimensional images with time correlation by using MTF. Then, the stripe pooling module (SPM) was presented and introduced into the network, which could not only enhance the ability of the model to capture information in the long-distance direction but also effectively extract remote spatial features. Secondly, the channel attention mechanism, namely SE was added before the max pooling layer to increase the weight of useful information and improve the training speed of the model. The MTF-SPCNN model was thus constructed. Finally, the MTF images were input into the MTF-SPCNN for training, and fault classification results were obtained. The data sets of Case Western Reserve University and laboratory rolling bearings MFS were used to verify the validity of the proposed method in small samples with variable load and variable speed, and the MFS data sets were processed with noise added and compared with other intelligent algorithms. Experimental results show that the proposed method has higher fault recognition accuracy and stronger generalization performance and anti-interference performance.

Due to its huge parameters and computational requirements, the lip reading model is not suitable for use with edge devices or mobile terminals. In order to solve this problem, we propose a lip reading method based on decoupled homogeneous self-knowledge distillation and GhostNet-TSM. First, the TSM module is installed into the GhostNet to extract temporal features. Second, the homogenous self-knowledge distillation is decoupled to increase the recognition accuracy of the model. Finally, the validation experiment on the LRW and LIP350 datasets has been completed and verified on the OuluVS dataset.The experimental results show that the recognition accuracy of GhostNet-TSM on the LRW dataset reaches 85.2%, which exceeds that of most non-lightweight models. The number of floating point operations per second and model parameters is reduced to 0.988 GFLOPs and 20.310×10⁶.

In order to select the optimal construction scheme during the construction process for different construction objectives in the airport runway project management, various construction schemes for the airport runway construction process were analyzed, and the mathematical models were established in terms of the construction period, quality, and cost. On this basis, the improved genetic algorithm was used, and the construction scheme for the airport runway construction process was taken as the optimization object. The construction period, quality, and cost were set as the optimization objectives, and a multi-objective optimization model of the airport runway construction scheme was constructed. Then, the general framework of object-oriented multi-objective optimization of airport runway construction schemes was built by using Python language, and the software interface development with the functions of parameter input, construction scheme optimization, and optimization result output was realized based on PyQt5. Finally, on the premise of meeting certain quality and cost, with the shortest construction period as the optimization objective, the optimization performance of the software was verified. The analysis of the optimization results shows that the application of the improved genetic algorithm can effectively achieve the multi-objective optimization of airport runway construction schemes. The optimization results are correct and meet the needs of optimization objectives, which can provide a reference for decision-making of airport runway construction projects.

In order to predict the output stability period of hemispherical resonator gyro (HRG) accurately, a stability period prediction method based on signal decomposition and classification modeling was proposed. The sample variation law is not obvious due to the characteristics of high reliability and long-term stability of HRG. To solve this problem, the complementary ensemble empirical mode decomposition (CEEMD) algorithm with the ability of a frequency microscope was used to decompose the output to obtain the signal components with different frequency scales. The augmented Dickey-Fuller (ADF) method was applied to test the stationarity of component signals. Auto regressive moving average model (ARMA) prediction model was established for stationary components, and the entropy-radial basis function (RBF) neural network model was established for non-stationary components. After time alignment, the component signals were reconstructed to obtain the gyro output prediction model. The gyro output stability standard was designed, and the stability period prediction flow based on output prediction was provided. The experimental results show that the average relative error of the combined model prediction is only 1.29%, which is one order of magnitude less than the error of the autoregressive integrated moving average model (ARIMA) and one time less than the error of the entropy-RBF network model, which verifies the effectiveness and high accuracy of signal decomposition and classification modeling methods. The gyro stability period is predicted based on the gyro prediction output, and the conclusion that the experimental gyro output stability period is 3.95 years is obtained, which is consistent with the practical application, indicating the feasibility of the proposed method.

Strong impact loading is applied to the site during the landing process of large helicopter. The dynamic interaction between a large helicopter and the landing site is significantly dependent on the property of the landing site. The small-scale model test was carried out by modeling the impact loadings of two wheels belonging to one dual-wheel landing gear on the loess site using the new double hammer impact testing equipment, which was based on the fixed landing situation of a big helicopter. The settlement and dynamic vertical stress produced in the loess site are analyzed together with the effects of hammer spacing. It is found that the settlement in the shallow layer of the loess site shows the typical W type under the impact of double hammers. Single pulse characteristics can be observed in the time history curve of dynamic vertical stress, which is comparable in different positions. The magnitude of the settlement and peak vertical stress along the centerline of the drop hammer decreases with increasing depth. However, their decreasing rate is related to the depth and the largest decreasing rate is produced in the shallow layer of the loess site. The hammer spacing mainly affects the magnitude of the settlement and dynamic vertical stress, which has minor effects on the variation pattern of the settlement and dynamic vertical stress.

In order to solve the problem of aircraft path conflict in autonomous operation mode, this paper proposed a multi-aircraft path game coordination method based on distributed decision-making. Firstly, a mixed strategy-evolutionary game model was constructed based on the path planning of aircraft operating in autonomous mode. The model was divided into two parts. Firstly, based on the idea of a mixed strategy game, the solution space of the aircraft path game was reduced by eliminating the game strategy that cannot reach the equilibrium state, and the solution process of the game problem was greatly simplified. Then, the game problem was regarded as an incomplete rational evolutionary game problem, and the evolution law of each aircraft path preference was set up. The equilibrium solution of the evolutionary game problem was solved. Finally, simulation experiments were carried out using the actual sector structure and data. The results show that the average path length of aircraft operating in autonomous mode only increases by 9.15%, but the peak air traffic complexity decreases by 30.15%, and the number of highly efficient grids in airspace increases by 26.46%. In the simulated environment of clear air turbulence and cabin decompression, the anti-disturbance capability of this path is significantly improved, and the number of disturbed aircraft decreases by 32.39% and 56.72%, respectively.

In recent years, video event detection has attracted increasing attention in the field of computer vision. Uncertainty estimation can alert decision-making systems or personnel when the output detection results are unreliable, reducing decision-making errors. In this paper, we proposed an end-to-end video event detection algorithm that fuses uncertainty estimation into the event detection task. The proposed algorithm estimates the localization and classification uncertainty for the input video events and optimizes network performance by reducing the predicted uncertainty. In addition, this paper combines uncertainty estimation with the Non-Maximum Suppression strategy to further filter the high-quality prediction boxes. The experimental results show that adding an uncertainty branch can improve the algorithm’s performance. On the J-HMDB-21 dataset, the proposed algorithm improves the mAP50 detection index by 0.8% compared with advanced algorithms. On the atomic visual actions (AVA) dataset, compared with other end-to-end networks, the mAP50 index is also improved by 1.3%.

To measure river parameters using global navigation satellite system-reflectometry (GNSS-R), this paper studies the coherence of the GNSS signal reflected offthe river surface, and the Doppler frequency shift of the GNSS signal relative to the direct signal, explores the methods of using GNSS-R to measure river boundary, water level, and water velocity, and conducted an experimental demonstration. To measure water level, a multi sample observation and two step fitting method are proposed to overcome the channel bias in the code phase altimeter and the outlier in the carrier phase.The research results show that there is no obvious Doppler freuqncy shift in the forward scattered signal, but there is a Doppler frequency shift phenomenon in the backward scattered GNSS signal, and the strong and weak coherent signals respectively dominate the forward scattered and backward scattered signals, so that the strong coherent signal in the forward scattered signal can be used to measure the river boundary and water level, while the backward scattered signal can be used to measure water velocity. The experimental results show that the reflected to direct power ratio from the river surface is larger than that from the river bank so that it is possible to measure river boundaries through detected mutation points of the reflected to direct power ratio in the specular point trajectories, and the measured water velocities of the B11 and B3I signals are 0.34 m/s and 0.51 m/s, respectively.

Depth information plays an important role in accurately understanding the three-dimensional scene structure and the three-dimensioual relationship between objects in images. An end-to-end self-supervised depth estimation algorithm based on uncertainty for monocular images was proposed in this paper by combining structure-from-motion, image reprojection, and uncertainty theory. The depth map of the target image was obtained by the encoder-decoder depth estimation network based on an improved densely connected module, and the transformation matrix of camera positions for shooting the target image and source image was calculated by the pose estimation network. Then, the source image was sampled pixel by pixel according to the image reprojection to obtain the reconstructed target image. The proposed algorithm was optimized by the reconstructed objective function, uncertain objective function, and smooth objective function, and the self-supervised depth information estimation was realized by minimizing the difference between the reconstructed image and the real target image. Experimental results show that the proposed algorithm achieves better depth estimation effects than the mainstream algorithms such as competitive collaboration estimation algorithm (CC), Monodepth2, and Hr-depth in terms of both objective indicators and subjective visual comparison.

Loop heat pipe possesses the advantages of no vibration, strong heat transfer capability, high temperature controlling accuracy, and long transmission distance, which is widely applied in the field of thermal control of spacecraft platforms and load. Temperature controlling accuracy and heat transfer limit, as key performance parameters of loop heat pipes, are the research focuses in the design and application of loop heat pipes. In this paper, the influence of attitude and temperature controlling position on temperature controlling accuracy of loop heat pipes was investigated. The results show that the attitude of loop heat pipes will affect gas-liquid distribution in the compensation chamber in the gravity environment. When the temperature controlling point is located in the saturated vapor zone in the compensation chamber, the temperature controlling accuracy is close to ±0.2 °C, which is higher than temperature controlling point in the pure-liquid zone (±0.6 °C). Meanwhile, the capillary limit prediction model of loop heat pipes is modified by analyzing gas-liquid distribution in capillary cores. The experimental results show that the modified model can predict the capillary limit of loop heat pipes well.

In view of the complex aerodynamic environment and noise characteristics of the scissors tail rotor under the condition of sideslip, an aeroacoustic prediction method was proposed based on computational fluid dynamics (CFD)/FW-H equation. Firstly, the flow field of the scissor tail-rotor was numerically simulated by solving the Reynolds averaged Navier-Stokes (RANS) equation. Then, the FW-H equation based on the integral surface of the solid surface was used to solve the aeroacoustic. Under sideslip circumstances, the aerodynamic and aeroacoustic properties of the standard tail rotor and the scissor tail rotor (L45) were examined. The numerical results show that with the increase of sideslip angle, the thrust fluctuation of the scissor tail-rotor increased more than that of the conventional tail-rotor. Under the same condition, the thrust fluctuation of a scissor tail-rotor is obviously larger than that of a conventional tail-rotor, which is generally more than 2 times. Therefore, the design should adequately account for the detrimental effects of the scissors tail rotor on the helicopter’s balance and control. In most states, the maximum total noise of a scissors tail-rotor is bigger than that of a conventional tail-rotor.

Calculating hinge moments during the morphing process is a critical link in the aircraft design with a folding wing. Existing simulations mostly use the traditional lifting surface method for aerodynamic modeling, which ignores the influence of the airfoil thickness and causes a great calculation error. This paper introduced a steady high-order panel method that considered the airfoil thickness and presented an aerodynamic modeling strategy using the high-order panel method to modify the thickness of the lifting surface method. The modified aerodynamic model was then coupled with the flexible multibody model and the flight control model to simulate the flight morphing process of a folding wing. The results show that the modified aerodynamic model can effectively consider the airfoil thickness, and the calculation error of the hinge moment is less than 5%.

As a necessary pneumatic deceleration system in the descent and landing process of the Mars probe, the demand for Mars parachutes for connection components with small mass and large loads is increasing. In view of this situation, this paper proposes a new type of flexible connection technology, which aims to the wear of flexible fabric and the weight of the system, and improve the load carrying load carrying capacity of the connection part. The research process adopted the method of two-step analysis combined with experimental verification. The numerical model of the flexible connection was first built using the lumped parameter approach, and the findings were then used as the finite element's boundary conditions to examine each joint's contact state. Finally, the strength of the parachute was verified by the test data, and the numerical simulation results are in good agreement with the test data. The findings demonstrate that, in comparison to metal components, the flexible connection technology parachute's strength is increased by 1.67 times, its weight is reduced by 58.3%, the strain at the contact position increases as the parachute's opening speed increases, and it can withstand the load associated with opening a parachute in a Mars-like environment. These findings could be a valuable design reference for future Mars parachutes.

Coreference resolution is an important task in the domain of natural language processing. Learning effective referential feature representation is a core problem of coreference resolution. It is ineffective to reflect the internal relationships between the information, such as named entities in text fragments and coreference pairs, because the majority of current research views the identification of reference text fragments and the prediction of coreference relationships as two stages of learning. This research proposes a new model of coreference resolution based on graph structure and multitask learning. It combines sequence semantics and structure information to learn referential feature vectors. A multitask learning framework is used to combine the two tasks of coreference resolution and named entity recognition. The two tasks, named entity recognition and coreference resolution, can learn from each other and get better at each other by sharing parameters in the underlying network. Extensive experiments are conducted to verify the superior performance of the proposed model.

Regarding the issue of transient heat flux measurement on the surface of hot end components of aero-engine, for an advanced thin-film heat flux sensor with a transverse temperature difference measurement structure, differential equations of transient thermal conductivity were established by adding the time term into the transient thermal conductivity model. The Laplace transform method and the deconvolution method were used to solve the thermal conductivity equations. The transient surface heat flow measurement method of the thin-film heat flux sensor was obtained and verified by numerical simulations. The results show that this method breaks through the limitation of the original steady state measurement and is suitable for the transient heat flow measurements on solid surfaces. The calculated surface heat flow of the heat flow meter is in good agreement with the true value. In particular, under the condition of surface step heat flow, the measurement accuracy is about 8.2%. Under the condition of sinusoidal heat flow at 100 Hz, the measurement accuracy is about 4.0%.

A hierarchical control strategy is proposed for distributed-driven vehicles, taking into account the powertrain dynamical hysteresis and the coordination of motor torques and wheel steerings. This is based on the coupling characteristics of vehicle planar motion in longitudinal, lateral, and yaw directions, as well as the hysteresis characteristics of electric driving and tire response. The dynamic hysteresis is simplified to the first-order inertial term of tire force, and combined with the planar motion model to establish an ascending-order vehicle dynamics model. Then a hierarchical coordinated control strategy is proposed, containing a reference state generator, a feedback trajectory tracking controller, and an optimal control allocator. To be more precise, the top layer uses a single-track model to convert the driver's commands into expected steady-state motion states. Next, the tracking controller is established using disturbance rejection model predictive control (DRMPC), and a lumped extended state observer (ESO) is used for disturbance observation and feedback compensation. A model predictive controller (MPC) is then introduced to produce generalized longitudinal force, lateral force, and yaw moment. Finally, the bottom layer executes optimal control allocation, decoupling motor torques and wheel angles using Jacobi linearization and treating them as equivalent control inputs in the optimal allocation with the goal of minimizing tire force utilization. Processor in the loop (PIL) experiments show that: dynamic hysteresis generates an obvious effect on vehicle planar motion; the proposed hierarchical control strategy presents advantages in control accuracy and response speed in the double-lane-change maneuver compared with conventional control strategy which ignores the hysteresis; in the constant-acceleration-sinusoidal-steering test, the proposed algorithm realizes planar motion control through control force redistribution, and the tire force loading rate is only 38.2% of the traditional rule-based allocation strategy.

Lean premixed pre-vaporized (LPP) combustion technology is widely used in centrally staged combustors of aero engines to reduce pollutant emissions. However, such combustors are prone to combustion instability. The control effect of the Helmholtz resonator on combustion oscillation in a central-staged LPP combustor of an aero-engine was studied. The experiment was carried out on a single-head model combustor with liquid aviation kerosene as fuel, involving two working conditions: medium temperature and medium pressure, as well as high temperature and high pressure. According to the acoustic simulation results, compact Helmholtz resonators were designed, with volumes of 80 mL and 160 mL. The experimental results show that Helmholtz resonators with a working frequency close to the combustion oscillation frequency can significantly reduce the oscillation amplitude. In the medium temperature and medium pressure experiment, the Helmholtz resonator can completely eliminate combustion oscillation under the condition of flame stage ratio of 25.1% and head equivalent ratio of 0.6. In the high temperature and high pressure experiment, the oscillation amplitude is reduced by about 90%. In addition, the reasonably designed resonator has slightly different control effects at different stage ratios, with a decrease in oscillation amplitude in the range of 69.9%～98.9%. Meanwhile, the acoustic simulation results show that the addition of a resonator has little effect on the acoustic characteristic modes of the system, which is consistent with the experimental results. In summary, the Helmholtz resonator with a compact structure has the potential to suppress combustion oscillations in an LPP combustor of aero-engine.

An essential part of space orbit competition research is the way the satellites swarm together to generate a round-up situation for space targets. The round-up situation can effectively support the satellite swarm to implement detection and perception with all-around and real-time performance and multi-angle pursuit-evasion game for space targets. Most of the existing research on the problem of space target pursuit-evasion was based on the differential game theory to establish the game model to solve one pursuit and one escape problem. It is a research difficulty for satellite swarms to cooperate and realize round-up in the form of groups. Aiming at the problem of rounding up a space target with a satellite swarm, a method based on a wolf pack optimization algorithm is proposed. Discrete the total duration of the round-up task into multiple decision-making cycles, and design a fitness function that comprehensively considers the position distribution of the satellite swarm, the round-up situation, the fuel consumption and safety collision avoidance. Control the satellite swarm to close to the target satellite and to distribute approximately evenly on the sphere with the target as the center via co-optimizing the thrust vector of satellite swarm in the decision-making cycle. The outcomes of the simulation demonstrate that the approach is capable of obtaining the satellite swarm's maneuvering strategy to swiftly round up the space target, create a round-up scenario, and efficiently support the space orbit competition task.

In view of the characteristics of complex maritime combat situations, diverse combat missions, and heterogeneous combat units of unmanned aerial vehicle (UAV) clusters, a multi-objective mission assignment optimization model for maritime UAV clusters was established, and an improved discrete particle swarm optimization algorithm based on $\gamma $ random search strategy (γ-DPSO) was proposed for this model. Firstly, the combat situation details and complex combat requirements were introduced into the mission assignment problem of UAV clusters, and a mission assignment combat model of UAV clusters that fitted the combat scenario was established. Secondly, based on the particle coding matrix, the equilibrium search strategy, the $\gamma $ random search strategy, and the phased adaptive parameters were designed, and the improved discrete particle swarm optimization algorithm based on the $\gamma $ random search strategy was proposed to solve the problem that the discrete particle swarm optimization algorithm was easy to fall into local optimum and caused immature convergence. The simulation results show that the proposed improved algorithm can effectively solve the multi-objective mission assignment problem of UAV clusters for the multi-objective mission assignment optimization model of UAV clusters established in this paper that meets the characteristics of maritime combat, and the proposed improved strategy improves the convergence speed and accuracy of the algorithm.

When the jammer executes the ground self-screening jamming and penetration action, the scintillation detection system of air-defense netted radars can guarantee the efficiency of cooperative detection of air-defense radars and improve the concealment of the system. An optimal scheduling model for scintillation detection of air-defense netted radars based on a multi-objective artificial bee colony (MOABC) algorithm was proposed. Firstly, the azimuth-range interval was processed, and the radar network detection responsibility area was divided into multiple grids. The jammer track was discretized, and the grid center point was approximated to the position of the jammer in different time slots. Then, the optimal scheduling model for scintillation detection of radar network was established, which took the threat degree of jammer, active detection time, and detection probability as optimization objectives. Finally, the MOABC algorithm was used to solve the radar scheduling scheme in a working state, and decimal integer encoding was adopted to reduce the search space dimension. The simulation results show that the optimized scheduling scheme can significantly improve the survivability of ground radar positions compared with other strategies and ensure the detection ability of radar networks.

The research on traffic situation awareness technology in terminal areas has made some achievements, but there is no clear method to optimize traffic situation in terminal areas with the help of this technology. In this paper, the concept of situation orientation in terminal areas was proposed, and the key technologies to achieve situation orientation were divided into three categories and elaborated respectively. Then, based on the traditional slot allocation model, a two-stage slot allocation mechanism was established by adding airlines’ preferences. In the first stage, a fair reference schedule was constructed for each airline; in the second stage, the reference schedule was adjusted to satisfy as many requests as possible from these airlines’ regarding the displacement of allocation in the schedule. The results of the example show that the schedule obtained according to the proposed slot allocation mechanism not only ensures fairness but also improves the acceptability of the airlines, and the positive effect of the mechanism on the traffic situation in busy terminal areas is analyzed.

The extreme high-temperature weather that has occurred worldwide in recent years has significantly increased the probability of lithium-ion batteries operating in high-temperature environments. The battery consistency difference caused by the operating environment and system management makes the battery prone to slight over-discharge. The coupling between high-temperature environment and over-discharge phenomenon significantly increases the risk of battery safety accidents. In order to study the influence of high-temperature environment and slight over-discharge coupling on the aging behavior of lithium-ion batteries, this paper carried out a slight over-discharge experiment on ternary lithium-ion batteries at 60 °C (high temperature) and 25 °C (normal temperature). The results show that the battery capacity attenuation rates after 100 cycles of slight over-discharge at 60 °C and 25 °C are 28.46% and 2.54%, respectively. Compared with that in normal temperature environments, slight over-discharge in high-temperature environments significantly increases the battery capacity attenuation. The electrochemical analysis of the battery shows that high temperatures limit the lithium deintercalation reaction inside the battery, increase the loss of active lithium, and degrade the kinetic performance. Battery disassembly photos, scanning electron microscopy, and elemental analysis results prove that slightly over-discharged batteries in high-temperature environments are severely deformed, and more sediments are produced by battery side reactions. Therefore, the coupling of a high-temperature environment and slight over-discharge will aggravate the damage of the cathode structure and internal side reactions, leading to a decline in battery performance. The research results can provide an experimental reference and theoretical basis for the development of lithium-ion battery materials and the safe operation of electric vehicles.

An ideal design approach is suggested for the trade-offs between performance and cost as well as between regional coverage and worldwide target coverage in the design of a constellation of remote sensing satellites. For the contradiction between construction cost and performance, a multi-objective optimization algorithm is used to optimize the cost and performance at the same time. The optimization results represent the increasing trend of performance and the possible conflicts between different performance indicators as the cost increases. A solution method based on the non-dominated sorting gonetic algorithims-II(NSGA-II) algorithm is suggested for this more flexible constellation model, which is used to meet specific limitations of the global coverage performance and improve the coverage performance of a particular area. The results show that after applying the new constellation model and algorithm, better performance can be achieved under the same constellation size or cost constraints.

The dynamic parameters of spacecraft with rotating flexible panels are uncertain. In view of this problem, a robust attitude controller design method based on linear parameter varying (LPV) theory was proposed. Firstly, the LPV model of attitude dynamics of flexible spacecraft was established by taking the angles of rotations of solar panels as the variable parameter. The limited input and rates of change of input signals were considered, and the quadratic control indicator limit was optimized. Based on the linear matrix inequality (LMI) method, An LPV state feedback controller with variable parameter scheduling was obtained. The obtained controller can maintain robust stability under the condition of a wide range of system parameters and has anti-interference ability. Finally, the simulation was verified by numerical method and compared with the steady robust controller. The adaptability and robustness of the proposed LPV robust controller were verified.

An enhanced version of the Speech Enhancement Generative Adversarial Network (SEGAN) algorithm used in air traffic control (ATC) is suggested in an effort to raise the standard of radiotelephony communication. Aiming at the problem that the traditional SEGAN is submerged under the condition of low signal-to-noise ratio, a multi-stage, multi-mapping, multi-dimensional output generation and multi-scale, multi-discriminator network models are proposed. First, the deep neural network structure is used to extract the speech semantic features, and the ATC speech semantic segmentation is finished. Secondly, set up multiple generators to further optimize the speech signal. Then, a down sampling module is added to the convolutional layer to improve the utilization of speech information by the model and reduce the loss of speech information. Finally, multi-scale, multiple discriminators are used to learn the distribution law and information of speech samples in multiple directions. According to the results, the improved SEGAN model's Short-Time Objective Intelligibility (STOI) and Perceptual Evaluation of Speech Quality (PESQ) are improved by 23.28% and 20.11%, respectively, under low signal-to-noise ratio conditions. This can effectively and swiftly improve ATC speech, making it a good option for follow-up. Provide preparatory work for subsequent Automatic Speech Recognition of ATC.

A two-body 9-degree of freedom (DOF) dynamics model of the parafoil system was established, and the Runge-Kutta method was used for dynamic programming calculation. The numerical results of the system velocities and parafoil and load attitudes were consistent with the results in the literature, and the maximum error was 8.2%. On this basis, the influence of hierarchical maneuvering and maneuvering velocity on the flared landing performance of the parafoil system was investigated. The variations of minimum horizontal velocity, minimum vertical velocity, and maximum angle of attack of parafoil were obtained. The results show that the flared landing performance under one-time maneuvering is better than that under hierarchical maneuvering. If the maneuvering duration is too long or too short, the vertical velocity will increase. Both maneuverings featuring first accelerating and then decelerating and constant velocity can ensure good flared landing performance. The minimum vertical velocity and the flight stability of the parafoil should both be considered in the selection of the maneuvering velocity.

The space locking mechanism always faces the problem of a long drive chain, as well as takes large physical space. In this work, a space repeatable mechanical locking and electromagnetic unlocking mechanism has been proposed on the basis of friction self-locking theory. Various finite element analysis software has been used to study the bearing capacity and electromagnetic property of the reusable locking mechanism. The results show that under the maximum axial locking load, the contact forces increase linearly with the increasing time between the steel locking ball and the pressing plate, the ejector pin, as well as the shell. It meets the transitivity criterion and the equilibrium criterion of force. The equivalent stress and deformation of the ejector pin and the lock bead are linear with time as well. The maximum equivalent stress is far less than the yield strength of the material and the device is in a small deformation range. When the rated current is applied to the coil, a stable ohmic loss occurs in the coil with equal current density due to the resistance heating effect. The electromagnetic unlocking technology maintains a roughly constant magnetic field inside. The magnetic agglomeration action in the iron core enhances the magnetic induction intensity on the end face. After the concept was established, a prototype for an electromagnetic unlocking and mechanical locking system in space was produced. This work presents a perspective on the design and analysis of the reusable locking mechanism for the on-orbital docking interfaces.