履带车辆转向期间的自动换档

讨论了履带车辆在转向期间实现换档的必要性和可能性,介绍了一个使用二级行星转向机的履带车辆,在转向期间自动换档的控制系统及其试车情况,并论述了采用双流转向机构后进行自动换档的控制策略。     

提问式教学法探讨

提问式教学法,不仅可以提高学生的注意力,激发学生的兴趣,而且有助于学生更好地消化、吸收知识。笔者从人的思维方式及心理活动特点入手,结合教学中的实践经验,阐述了提问式教学方法的特点以及在实践中的具体运用,对该教学法进行了较为深入的探讨。     

基于XilinxFPGA的数字下变频的实现

为解决专用数字下变频芯片价格昂贵、灵活性不强的问题,研究了如何基于FPGA实现数字下变频的功能。本设计结合硬件资源从数字下变频的系统各模块的主要功能,以及从彼此间的性能制约上考虑,先通过MATLAB仿真选择合适的参数,然后在Xilinx公司ISES．2开发环境下,使用Verifog语言编程实现。最后对基于FPGA实现的数字下变频系统调用Modelsim进行仿真测试,验证了设计的正确性。     

An efficient SPH methodology for modelling mechanical characteristics of particulate composites

Particulate composites are one of the widely used materials in producing numerous state-of-the-art components in biomedical, automobile, aerospace including defence technology. Variety of modelling techniques have been adopted in the past to model mechanical behaviour of particulate composites. Due to their favourable properties, particle-based methods provide a convenient platform to model failure or fracture of these composites. Smooth particle hydrodynamics (SPH) is one of such methods which demonstrate excellent potential for modelling failure or fracture of particulate composites in a Lagrangian setting. One of the major challenges in using SPH method for modelling composite materials depends on accurate and efficient way to treat interface and boundary conditions. In this paper, a master-slave method based multi-freedom constraints is proposed to impose essential boundary conditions and interfacial displacement constraints in modelling mechanical behaviour of composite materials using SPH method. The proposed methodology enforces the above constraints more accurately and requires only smaller condition number for system stiffness matrix than the procedures based on typical penalty function approach. A minimum cut-off value-based error criteria is employed to improve the compu-tational efficiency of the proposed methodology. In addition, the proposed method is further enhanced by adopting a modified numerical interpolation scheme along the boundary to increase the accuracy and computational efficiency. The numerical examples demonstrate that the proposed master-slave approach yields better accuracy in enforcing displacement constraints and requires approximately the same computational time as that of penalty method.     

Maneuvering target tracking of UAV based on MN-DDPG and transfer learning

Tracking maneuvering target in real time autonomously and accurately in an uncertain environment is one of the challenging missions for unmanned aerial vehicles(UAVs).In this paper,aiming to address the control problem of maneuvering target tracking and obstacle avoidance,an online path planning approach for UAV is developed based on deep reinforcement learning.Through end-to-end learning powered by neural networks,the proposed approach can achieve the perception of the environment and continuous motion output control.This proposed approach includes:(1)A deep deterministic policy gradient(DDPG)-based control framework to provide learning and autonomous decision-making capa-bility for UAVs;(2)An improved method named MN-DDPG for introducing a type of mixed noises to assist UAV with exploring stochastic strategies for online optimal planning;and(3)An algorithm of task-decomposition and pre-training for efficient transfer learning to improve the generalization capability of UAV's control model built based on MN-DDPG.The experimental simulation results have verified that the proposed approach can achieve good self-adaptive adjustment of UAV's flight attitude in the tasks of maneuvering target tracking with a significant improvement in generalization capability and training efficiency of UAV tracking controller in uncertain environments.     

An experiment evaluating how the tiny mass eccentricities in spin-stabilized projectiles affect the position of impact points

This study investigates and quantifies some possible sources affecting the position of impact points of small caliber spin-stabilized projectiles (such as 12.7 mm bullets). A comparative experiment utilizing the control variable method was designed to figure out the influence of tiny eccentric centroids on the projectiles. The study critically analyzes data obtained from characteristic parameter measurements and precision trials. It also combines Sobol's algorithm with an artificial intelligence algorithm—Adaptive Neuro-Fuzzy Inference Systems (ANFIS)—in order to conduct global sensitivity analysis and determine which parameters were most influential. The results indicate that the impact points of projectiles with an entry angle of 0° deflected to the left to that of projectiles with an entry angle of 90°. The difference of the mean coordinates of impact points was about 12.61 cm at a target range of 200 m. Variance analysis indicated that the entry angle — i.e. the initial position of mass eccentricity — had a notable influence. After global sensitivity analysis, the significance of the effect of mass eccentricity was confirmed again and the most influential factors were determined to be the axial moment and transverse moment of inertia (Izz Iyy), the mass of a projectile (m), the distance between nose and center of mass along the symmetry axis for a projectile (Lm), and the eccentric distance of the centroid (Lr). The results imply that the control scheme by means of modifying mass center (moving mass or mass eccentricity) is promising for designing small-caliber spin-stabilized projectiles.     

Mitigation effects on the reflected overpressure of blast shock with water surrounding an explosive in a confined space

The mitigation of blast shock with water has broad application prospects. Understanding the mitigation effects on the reflected overpressure of the explosion shock with water surrounding an explosive in a confined space is of great significance for military explosives safety applications. To estimate the effects of the parameters on the reflected overpressure of blasted shock wave, a series of experiments were carried out in confined containers with spherical explosives immersed in a certain thickness of water, and numerical simulations were conducted to explore the corresponding mechanisms. The results reveal that the reflected overpressure is abnormally aggravated at a small scaled distance. This aggravation is due to the high impulse of the bulk accelerated water shell converted from the explosion. With increasing scaled distance, the energy will be gradually dissipated. The mitigation effects will appear with the dispersed water phase front impacting at a larger scaled distance, except in the case of a dense water phase state. A critical scaled distance range of 0.7—0.8 m/kg1/3 for effective mitigation was found. It is suggested that the scaled distance of space walls should be larger than the critical value for a certain water-to-explosive weight ratio range (5—20).     

Recent progress on transition metal oxides and carbon-supported transition metal oxides as catalysts for thermal decomposition of ammonium perchlorate

As a main oxidizer in solid composite propellants, ammonium perchlorate (AP) plays an important role because its thermal decomposition behavior has a direct influence on the characteristic of solid com-posite propellants. To improve the performance of solid composite propellant, it is necessary to take measures to modify the thermal decomposition behavior of AP. In recent years, transition metal oxides and carbon-supported transition metal oxides have drawn considerable attention due to their extraor-dinary catalytic activity. In this review, we highlight strategies to enhance the thermal decomposition of AP by tuning morphology, varying the types of metal ion, and coupling with carbon analogue. The enhanced catalytic performance can be ascribed to synergistic effect, increased surface area, more exposed active sites, and accelerated electron transportation and so on. The mechanism of AP decom-position mixed with catalyst has also been briefly summarized. Finally, a conclusive outlook and possible research directions are suggested to address challenges such as lacking practical application in actual formulation of solid composite propellant and batch manufacturing.     

Bidirectional parallel multi-branch convolution feature pyramid network for target detection in aerial images of swarm UAVs

In this paper, based on a bidirectional parallel multi-branch feature pyramid network (BPMFPN), a novel one-stage object detector called BPMFPN Det is proposed for real-time detection of ground multi-scale targets by swarm unmanned aerial vehicles (UAVs). First, the bidirectional parallel multi-branch convolution modules are used to construct the feature pyramid to enhance the feature expression abilities of different scale feature layers. Next, the feature pyramid is integrated into the single-stage object detection framework to ensure real-time performance. In order to validate the effectiveness of the proposed algorithm, experiments are conducted on four datasets. For the PASCAL VOC dataset, the proposed algorithm achieves the mean average precision (mAP) of 85.4 on the VOC 2007 test set. With regard to the detection in optical remote sensing (DIOR) dataset, the proposed algorithm achieves 73.9 mAP. For vehicle detection in aerial imagery (VEDAI) dataset, the detection accuracy of small land vehicle (slv) targets reaches 97.4 mAP. For unmanned aerial vehicle detection and tracking (UAVDT) dataset, the proposed BPMFPN Det achieves the mAP of 48.75. Compared with the previous state-of-the-art methods, the results obtained by the proposed algorithm are more competitive. The experimental results demonstrate that the proposed algorithm can effectively solve the problem of real-time detection of ground multi-scale targets in aerial images of swarm UAVs.     

航空用复合材料结构件无损检测技术分析

本文通过对航空复合材料结构件缺陷和损伤特点的分析,介绍可应用于航空复合材料结构缺陷包括目视检查法、声阻法、射线检测技术、超声检测技术、声-超声技术、涡流检测技术、微波检测技术在内的无损检测技术。并对无损检测技术的技术关键进行剖析,展望了无损检测技术的未来发展。