振梁加速度计温度误差模型及补偿技术研究

研究了振梁加速度计温度误差建模及补偿问题。分析了振梁加速度计受温度影响的主要因素,应用最小二乘算法得到零偏、标度因数与温度的多项式拟合关系,进而得到振梁加速度计的温度误差模型。利用该误差模型进行温度补偿。结果表明：经过温度建模和补偿,振梁加速度计精度有明显的提高。     

激光陀螺磁特性研究

本文分析了激光陀螺磁敏感原理,研究了腔内激光束椭偏度的产生机理,设计了高消光比激光束椭偏度测量系统。实验结果表明,激光陀螺磁灵敏度大小与磁场方向有关,输出激光束的椭偏度越大,磁灵敏度越大。研究表明,通过减小输出激光束的椭偏度,可减小激光陀螺磁灵敏度,从而增强激光陀螺环境适应性,提高激光陀螺的成品率。     

Imaging of target with complicated motion using ISAR system based on IPHAF-TVA

The technique of imaging a target with a complicated motion using an Inverse Synthetic Aperture Radar (ISAR) system is an effective tool in the field of radar signal processing. After the translational compensation, the received signal reflected from the target can take the form of a multi-component Polynomial Phase Signal (m-PPS), and the high quality ISAR image can be provided via the combination between the estimated parameters of the m-PPS and the Range Instantaneous-Doppler technique (RID). For a target with a high maneuvrability, the occurrence of scatterers Migration Through Resolution Cell (MTRC), caused by the rotational movement could be appearing. That is why the variation in the amplitude of the echo during the time of observation cannot be neglected. The purpose of this study is the parameters estimation of the m-PPS signal with order three in the case of the Time Varying Amplitude (TVA). The Improved-version of the Product High-order Ambiguity Function (IPHAF) with TVA is proposed to improve the quality of the ISAR image compared with traditional techniques based on a constant amplitude; the experimental outcomes confirm that the new IPHAF-TVA method presented in this study is an effective technique to make the ISAR image very clear.     

Effect of scavenge port angles on flow distribution and performance of swirl-loop scavenging in 2-stroke aircraft diesel engine

Swirl-Loop Scavenging (SLS) improves the performance of 2-stroke aircraft diesel engine because the involved swirl may not only benefit the scavenging process, but also facilitate the fuel atomization and combustion. The arrangement of scavenge port angles greatly influences in-cylinder flow distribution and swirl intensity, as well as the performance of the SLS engine. However, the mechanism of the effect and visualization experiment are rarely mentioned in the literature. To further investigate the SLS, Particle Image Velocimetry (PIV) experiment and Computational Fluid Dynamics (CFD) simulation are adopted to obtain its swirl distribution characteristics, and the effect of port angles on scavenging performance is discussed based on engine fired cycle simulation. The results illustrate that Reynolds Stress Turbulence model is accurate enough for in-cylinder flow simulation. Tangential and axial velocity distribution of the flow, as well as the scavenging performance, are mainly determined by geometric scavenge port angles α_geom and β_geom. For reinforcement of scavenging on cross-sections and meridian planes, α_geom value of 27° and β_geom value of 60° are preferred, under which the scavenging efficiency reaches as high as 73.7%. Excessive swirl intensity has a negative effect on SLS performance, which should be controlled to a proper extent.     

Towards intelligent design optimization: Progress and challenge of design optimization theories and technologies for plastic forming

Plastic forming is one of enabling and fundamental technologies in advanced manufacturing chains. Design optimization is a critical way to improve the performance of the forming system, exploit the advantages of high productivity, high product quality, low production cost and short time to market and develop precise, accurate, green, and intelligent (smart) plastic forming technology. However, plastic forming is quite complicated, relating to multi-physics field coupling, multi-factor influence, multi-defect constraint, and triple nonlinear, etc., and the design optimization for plastic forming involves multi-objective, multi-parameter, multi-constraint, nonlinear, high-dimensionality, non-continuity, time-varying, and uncertainty, etc. Therefore, how to achieve accurate and efficient design optimization of products, equipment, tools/dies, and processing as well as materials characterization has always been the research frontier and focus in the field of engineering and manufacturing. In recent years, with the rapid development of computing science, data science and internet of things (IoT), the theories and technologies of design optimization have attracted more and more attention, and developed rapidly in forming process. Accordingly, this paper first introduced the framework of design optimization for plastic forming. Then, focusing on the key problems of design optimization, such as numerical model and optimization algorithm, this paper summarized the research progress on the development and application of the theories and technologies about design optimization in forming process, including deterministic and uncertain optimization. Moreover, the applicability of various modeling methods and optimization algorithms was elaborated in solving the design optimization problems of plastic forming. Finally, considering the development trends of forming technology, this paper discusses some challenges of design optimization that may need to be solved and faced in forming process.     

Relevant experience learning: A deep reinforcement learning method for UAV autonomous motion planning in complex unknown environments

Unmanned Aerial Vehicles (UAVs) play a vital role in military warfare. In a variety of battlefield mission scenarios, UAVs are required to safely fly to designated locations without human intervention. Therefore, finding a suitable method to solve the UAV Autonomous Motion Planning (AMP) problem can improve the success rate of UAV missions to a certain extent. In recent years, many studies have used Deep Reinforcement Learning (DRL) methods to address the AMP problem and have achieved good results. From the perspective of sampling, this paper designs a sampling method with double-screening, combines it with the Deep Deterministic Policy Gradient (DDPG) algorithm, and proposes the Relevant Experience Learning-DDPG (REL-DDPG) algorithm. The REL-DDPG algorithm uses a Prioritized Experience Replay (PER) mechanism to break the correlation of continuous experiences in the experience pool, finds the experiences most similar to the current state to learn according to the theory in human education, and expands the influence of the learning process on action selection at the current state. All experiments are applied in a complex unknown simulation environment constructed based on the parameters of a real UAV. The training experiments show that REL-DDPG improves the convergence speed and the convergence result compared to the state-of-the-art DDPG algorithm, while the testing experiments show the applicability of the algorithm and investigate the performance under different parameter conditions.     

Preparation of CF/Ni-Fe/CNT/silicone layered rubber for aircraft sealing and electromagnetic interference shielding applications

To meet the needs of preventing information leakage in space engineering and military industry, an efficient method was introduced to obtain layered electromagnetic shielding sealing rubber. The carbon fiber, Ni-Fe coating, and Carbon NanoTube (CNT) were combined by chemical plating and in-situ polymerization to obtain a lightweight (0.14 g/cm²) and thin (1 mm thick) Carbon fiber Fabric (CF)/Ni-Fe/CNT/silicone layered electromagnetic shielding composites. The layered material obtained by adjusting the electroless plating time exhibited a high Shielding Efficiency (SE) of 60.2–85.5 dB in the range of 0–4800 MHz, which can be used for aviation electromagnetic shielding. Carbon fibers and carbon nanotubes mainly attenuated electromagnetic waves through absorption loss, while the nickel-iron alloy coating through reflection loss interacted with the magnetic vector of incident ElectroMagnetic (EM) radiation and magnetic dipoles, therefore, the EM Interference (EMI) shielding composite attenuated EM waves with the “absorption-reflection-absorption” cooperative interaction. Moreover, the flexible fabric substrate adhered with silicone rubber possessed a breaking elongation of 52.3%, which can be utilized as a good sealing material. Simultaneously, the outstanding exothermicity (67.2 °C under the applied voltage of 5 V) makes it possible to be applied in electric heating area. The electromagnetic shielding composites prepared in this paper have good potential in the fields of precision electronic equipment and aviation systems.     

复杂大时延的多主多从共享遥操作方法

共享遥操作结合了遥操作和多机器人协调技术,是重要的空间机器人复杂任务拓展和遥操作可靠性提升方式。首先,在综述现有共享遥操作技术的基础上,利用遥操作系统的超前预报特性,提出机器人复杂大时延的共享遥操作方法,给出了多操作员多机器人（MM/MS）复杂操作系统描述模型,设计了分时树状分组策略并给出其使用的前提条件。提出了MM/MS组间共享遥操作方法、时延信息维护规则、操作请求判断和状态信息维护方法。然后,给出了相应组内共享遥操作算法。最后,以多操作员单机器人（MM/SS）共享遥操作为例,给出了简化规则,使用以某大型空间机械臂为对象的MM/SS遥操作系统进行了数字仿真实验。实验结果表明：本文方法在20 s级不确定时延、操作端的交互时延与遥操作回路时延比为0~1等复杂条件下,均可实施连续稳定的遥操作。     

民用飞机预研论证权威真相源构建技术

权威真相源不仅是基于模型的系统工程实施的核心要素,也是"数字工程战略"的关键环节。对权威真相源构建技术进行了研究,包括对权威真相源进行了定义和分析,设计了权威真相源的构建目标和原则,构建了权威真相源的架构和业务流程,并对构建权威真相源的支持技术进行了研究。梳理了民用飞机预研论证的业务流程、专业模型和基础模型,最后通过民用飞机预研论证验证机的案例研究,证实了权威真相源构建技术的可行性。民用飞机预研论证权威真相源能够有效提升系统工程的组织性,提升协同设计效率,同时能够提高模型和系统设计的重用性,减少系统工程实施的复杂度,缩小开发成本。     

飞行器径向连接螺栓振动断裂分析

应用有限元分析结合试验数据,获得随机振动环境下飞行器径向连接螺栓的载荷功率谱密度（PSD）;采用基于弯曲效应的载荷与应力的线性关系,获取螺栓头根部的名义应力功率谱密度;基于Dirlik经验公式,获取应力随机过程的峰值概率密度函数和预期波峰数,联合Miner线性累积损伤模型及经应力集中系数修正的材料S-N曲线,评估径向连接螺栓头根部振动疲劳寿命,获得的结果与试验螺栓头断裂现象符合,并确定螺栓断裂原因为低频共振疲劳。