To address the issue of harmonic concentration near fixed switching frequencies caused by high-speed switching actions in traditional PWM strategy, the random modulation strategies in the PMSM servo drive system are studied. On the basis of conventional RSF-PWM strategy, DRM-PWM strategy enhances EMC by introducing randomization of the zero-vector action time. However, this strategy struggles to balance EMI suppression effectiveness with system control performance. Subsequently, MARSF-SVPWM strategy is investigated, with a focus on comparing and analyzing the two modulation strategies. Compared to DRM-PWM strategy, MARSF-SVPWM strategy maintains overall spread spectrum range and average switching frequency while narrowing the distribution range of differences between adjacent switching frequencies, thereby further reducing harmonic peaks. Simulation and experimental results demonstrate that MARSF-SVPWM strategy achieves better harmonic dispersion performance compared to DRM-PWM, and maintains a lower impact on system control performance, optimizing the EMI suppression effect.

To address the limitations of existing methods for underwater unmanned vehicle (UUV) motor fault diagnosis, which rely on manual feature extraction and do not fully leverage the potential of intelligent diagnosis, a two-stream CNN-LSTM fault diagnosis model is proposed. The model employs convolutional neural networks as feature extractor, which can learn the low frequency trend and high frequency detail features of the original signal without complex pre-processing steps, making real-time motor status monitoring possible. Afterwards, the classifier based on the long short-term memory network uses these features to explore temporal dependencies and identify motor faults. Experiments are conducted on a self-constructed UUV motor fault simulation platform, and the performance of the model is validated by setting multiple speeds and load conditions. The results show that this method can efficiently diagnose six typical states in UUV motors and achieve an average diagnostic accuracy of 97.22%. These findings demonstrate the model's effectiveness and robustness in UUV motor fault diagnosis.

The rolling screw transmission mechanism is a key transmission component of the servo mechanism. Monitoring its operating state is crucial for the normal operation of the servo control system. Currently, there are still difficulties in the state monitoring of rolling screw transmission mechanisms, such as low integration and wiring difficulties. A multi-parameter wireless micro-nano sensing monitoring system for rolling screw transmission mechanisms is designed. The sensing module, MCU module, wireless module and power management module are integrated in this system, which can be integrated with the nut of the rolling screw transmission mechanisms directly and flexibly, improving integration and reducing wiring complexity. The sensing module contains three types of MEMS sensors for temperature, acceleration, and acoustics to meet the condition monitoring requirements of multi-point distributed and multi-parameter sensing on the surface and interior of the nut. This system has advantages of small size, easy installation, flexibility and high integration, effectively monitoring the working state of rolling screw transmission mechanisms.

This article takes the real-time intelligent reconnaissance of the American "Black Swift" hypersonic intelligent aircraft as an example to analyze the demand for strong real-time, high-energy efficiency intelligent computing of typical intelligent hypersonic vehicles. On this basis, it analyzes in detail how to build a strong real-time, high-energy efficiency intelligent computing system for intelligent hypersonic vehicles from three levels: intelligent model lightweight, software and hardware collaborative compilation and optimization, and ultra-heterogeneous integrated computing hardware. Furthermore, a system integration example is provided to illustrate the practical application of these principles. In the future, with the loading of the strong real-time, high-energy efficiency intelligent computing system, intelligent hypersonic aircraft will be more autonomous, reliable and capable of group collaboration, and will drive the intelligent upgrade of aerospace cross-domain flight and global rapid transit.

Aiming at the problem of difficulty in quickly and accurately estimating the pose of non-cooperative structures of satellites during the operation of space robotic arms, a neural radiation field based method for estimating and tracking the pose of non-cooperative key structures of satellites is proposed. This method first obtains the scene point cloud online through an RGBD camera, segments the point cloud to obtain satellite key structures, and then uses neural radiation fields to automatically establish a three-dimensional model of the key structures. Finally, based on the initial pose generation network and pose evaluation network, accurate pose estimation is obtained. An experimental platform consisting of an RGBD depth camera, a robotic arm, and a satellite model is constructed to conduct pose estimation experiments on key structures of satellites with different poses. The experimental results show that the algorithm proposed can automatically construct a 3D model of non-cooperative targets online without the need for human preparation of target data in advance. At the same time, it can effectively deal with target object occlusion and motion situations, thus achieving true non cooperative target pose estimation and tracking in spatial operations.

At present, with the complex and changeable game environment, deep learning models such as deep convolutional neural networks are introduced to assist in improving personnel's cognition and decision-making level of the game situation. However, when deep learning is introduced into game situation understanding, it also introduces data uncertainty and cognitive uncertainty in artificial intelligence, which leads to problems such as divergence of artificial intelligence prediction results. Key elements of uncertainty in the measurement process of game situation understanding are decomposed, extracted and measurement modeling constructed based on the measurement uncertainty evaluation method. The experimental results show that the physical measurement method based on GUM can effectively measure and evaluate the cognitive uncertainty of game situation accurately and efficiently. Finally, based on Monte Carlo method, the proposed new qualitative measurement method of game situation cognition uncertainty is verified, which shows the accuracy and applicability of the proposed method.

Numerical investigation on the characteristics of a two-dimensional, mixed-compression inlet with various leading edge bluntness is presented. Effects of leading edge bluntness on the self-starting ability, aerodynamic performance of the inlet at design and off design operations are acquired. Results indicate that, with the increase of blunted radius, the self-starting ability and mass flow capture of the inlet are deteriorated, the backpressure tolerance capability and critical total pressure recovery coefficient goes down, while the drag coefficient rises obviously. 5% decrease of mass flow ratio is observed while the backpressure tolerance and critical total pressure recovery coefficient drop off at least 8.5% for the design operating point. Complex shock wave interference pattern forms due to the oblique shock waves from the external compression of the inlet intersecting the bow shock wave produced in front of the leading edge with the variation of freestream Mach number and the angle of attack. Diminution of flow separation in the inner side of the inlet lip is observed with the increase of blunted radius at a high Mach number condition. As the angle of attack rises, the influence of the bow shock wave induced by the blunted leading edge on the performance of the inlet is found to be weaken.

Composite materials used in engineering design often exhibit different properties in tension and compression in addition to anisotropy. The tensile and compressive anisotropy of constitutive behavior can affect the stress and strain distribution of composite structures under operating conditions, further consideration of the difference between tension strength and compression strength may have an impact on the strength analysis results of the structure. This article takes the carbon-carbon composite material air rudder shaft as the research object, implements secondary development through ABAQUS' USDFLD interface, compares and analyzes the changes in rudder shaft stress before and after considering tensile and compressive anisotropy. Then, considering the tensile, compressive and in-plane shear strength of the material, corresponding stiffness reduction models are introduced to analyze the failure process of the rudder shaft under bending and shear loads. The analysis results indicate that different properties in tension and compression will have a significant impact on the stress distribution of composite structures, and this analysis method can achieve more accurate simulation of the failure process of the rudder shaft.

For higher reliability, higher efficiency and easier maintenance, three TVC actuators for a hydrolox launch vehicle block are studied comparatively, in aspects of designs, models and testing performances, namely, a Servo-Valve Controlled Electro-Hydraulic Actuator (SHA), an Electro-Mechanical Actuator (EMA) and an Electro-Hydrostatic Actuator (EHA), each outputting a peak power of 3 kW. A fully packaged duplex EHA design is proposed, lightweight and compact by means of innovating indepth integrations in the actuator, Electro-Hydrostatic Module (EHM), Servo Motor Pumps (SMPs) and Electronic Control Units (ECUs). The weight of a TVC system with four EHAs is 85 kg, reduced by 37%, compared to the SHA counterpart of 135 kg. The dynamic capability of three TVC actuators is almost on a par, with the first-order frequency bandwidth of greater than 30 rad/s. As to the overall efficiency of energy conversion, it is one order of magnitude higher for an EMA or an EHA than a SHA. In an operation profile on ground with a duration of 1 200 s, the efficiency is lowest for an SHA, less than 1%, and heated quickly, with the temperature reaching over 100 ℃ at the hydraulic pump. In contrast, as to the EMA and EHA,the efficiency is remarkably upgraded to over 20%, with the temperature only slightly increasing by 5 ℃ at the pump or the electric motor. It demonstrates that an EHA embodies both the heavy loading, high reliability of a SHA, and the high efficiency, good maintenance of an EMA, at the same time overcoming the weak points in dynamics, power density, oil sealing, etc., providing an intriguing option for highly reliable and secure launch vehicles. The EHA has finished its maiden flight as the first one for launch vehicles.

The cryogenic coupling is the key equipment between the rocket and the ground filling system. It is mainly used for the filling, draining,venting of cryogenic propellant, such as liquid hydrogen, liquid oxygen, liquid methane, etc. The sealing reliability of the cryogenic coupling is crucial to the launch mission. According to the application characteristics of cryogenic coupling, the performance parameters and structural parameters of the metal bellows are proposed.The stiffness, strength and fatigue life of the metal bellows are obtained by theoretical calculation. The stress distribution, contact state, stiffness and residual deformation of the metal bellows at normal temperature are obtained by simulation analysis, and the influence of low temperature on the stress and stiffness of the metal bellows is analyzed. The stiffness test, life test and performance tests of the cryogenic coupling are carried out, and the test data are in good fit with theoretical calculation and simulation analysis. The feasibility of the application of the metal bellows in cryogenic couplings for the seal compensation is verified.