成组技术中计算机辅助零件分类方法的探讨

成组技术是有效实现CAD/CAM的基础之一,是提高多品种、中小批量生产水平的重要手段。本文提出了在成组技术中应用模糊数学理论进行计算机辅助零件分类的新方法,并对回转零件进行了分类试验,取得了满意的结果。采用这种方法,不需要对零件进行编码,可以对零件相似性进行定量分析,使得零件分类更具有柔性,为成组技术中零件分类提供了新的方法。     

多尺度子域基函数矩量法解的稳定性与迭代法

通过对几个具体实例的计算，证实了在电磁场边值问题的矩量法求解过程中，选用不同的基函数其解的数值稳定性会有很大的差别。从而有可能选择一种数值稳定性比较好的基函数来进行矩量法求解。另一方面，提出了选用多尺度子域基函数，并通过多次迭代来提高矩量法解的精度的算法。实例计算表明，该算法不仅可以有效地降低系数矩阵的条件数，而且还降低了对计算机内存容量的要求，是一种有效的、稳定的算法     

火箭发动机基于神经网络非线性辨识的故障检测

应用神经网络方法，提出了一种液体火箭发动机故障实时检测算法。神经网络采用非线性辨识技术贴近发动机的工作过程，并输出包合发动机故障信息的辨识误差信号。若辨识误差变大超过一定阈值，检测逻辑就预报发动机故障。在发动机启动阶段离线训练神经网络，在发动机稳态过程可以采用离线或在线学习算法。实验研究表明神经网络可以成功地应用于大型泵压式液体火箭发动机的故障检测。     

微型脉冲推力器点火启动过程计算与点火药量选择

建立了微型脉冲推力器点火启动模型,模型中考虑了两相流动和颗粒对推进剂表面的冲击传热。根据数值计算结果,给出了不同产物颗粒含量下的点火药量选择参考范围。该参考范围对于产物颗粒含量小于50%的点火药是适用的;由于过多的颗粒含量将对装药表面产生强烈的热力冲蚀破坏作用,产物颗粒含量超过50%的点火药不适合微型火箭发动机。     

固体发动机喷管延伸锥展开前级间分离的热环境分析

通过FLUENT流场计算软件,采用RNGK k-ε湍流模型,针对带有延伸喷管的多级固体发动机级间热分离的热环境进行了数值分析。研究表明,延伸喷管尾流受到连接筒、前封头、延伸段的阻碍后,其流动特征变化显著,尤其在一级前封头的影响下形成回流,并在喷管内形成激波。计算得到的热环境参数,对发动机的热防护设计具有一定的参考价值。     

一种新型综合性靶场安全系统及其检验测试结果

本文首先简要介绍战略导弹发射场和航天发射场靶场安全系统的作用、特点、主要技术要求,接着介绍按美国空军航天司令部要求,由空军研究所开发的基于GPS弹道测量技术,外测、遥测、遥控综合为一体的机动型靶场安全系统——BMRST的构成及其经多种检验测试的结果。     

月面上升的轨迹优化与参数分析

面向月球采样返回任务分析需求,对月面上升段的轨迹优化及燃料消耗影响因素进行了研究。基于上升器运动模型,建立以燃料消耗最优为目标考虑入轨约束的轨迹优化模型,通过Gauss伪谱法和序列二次规划求解上升过程最优推力方向。改变运动模型中的初始推重比、入轨约束中的目标轨道参数,根据轨迹优化结果得到对应的燃料消耗,分析了这些因素对上升器燃料消耗的影响。针对上升器非共面起飞的问题,提出了上升偏航、升交点调整、倾角调整3种方案,从燃料消耗的角度分析了各方案的适用情况,为未来工程应用提供参考。     

A new modeling scheme for powered parafoil unmanned aerial vehicle platforms: Theory and experiments

A novel framework is established for accurate modeling of Powered Parafoil Unmanned Aerial Vehicle (PPUAV). The model is developed in the following three steps: obtaining a linear dynamic model, simplifying the model structure, and estimating the model mismatch due to model variance and external disturbance factors. First, a six degree-of-freedom linear model, or the structured model, is obtained through dynamic establishment and linearization. Second, the data correlation analysis is adopted to determine the criterion for proper model complexity and to simplify the structured model. Next, an active model is established, combining the simplified model with the model mismatch estimator. An adapted Kalman filter is utilized for the real-time estimation of states and model mismatch. We finally derive a linear system model while taking into account of model variance and external disturbance. Actual flight tests verify the effectiveness of our active model in different flight scenarios.     

Comparison of vertical E × B drift velocities and ground-based magnetometer observations of DELTA H in the low latitude under geomagnetically disturbed conditions

In the present work, we analyzed the daytime vertical E × B drift velocities obtained from Jicamarca Unattended Long-term Ionosphere Atmosphere (JULIA) radar and ΔH component of geomagnetic field measured as the difference between the magnitudes of the horizontal (H) components between two magnetometers deployed at two different locations Jicamarca, and Piura in Peru for 22 geomagnetically disturbed events in which either SC has occurred or Dst_max < ?50 nT during the period 2006–2011. The ΔH component of geomagnetic field is measured as the differences in the magnitudes of horizontal H component between magnetometer placed directly on the magnetic equator and one displaced 6–9° away. It will provide a direct measure of the daytime electrojet current, due to the eastward electric field. This will in turn gives the magnitude of vertical E × B drift velocity in the F region. A positive correlation exists between peak values of daytime vertical E × B drift velocity and peak value of ΔH for the three consecutive days of the events. It was observed that 45% of the events have daytime vertical E × B drift velocity peak in the magnitude range 10–20 m/s and 20–30 m/s and 20% have peak ΔH in the magnitude range 50–60 nT and 80–90 nT. It was observed that the time of occurrence of the peak value of both the vertical E × B drift velocity and the ΔH have a maximum (40%) probability in the same time range 11:00–13:00 LT. We also investigated the correlation between E × B drift velocity and D_st index and the correlation between delta H and D_st index. A strong positive correlation is found between E × B drift and D_st index as well as between delta H and D_st Index. Three different techniques of data analysis – linear, polynomial (order 2), and polynomial (order 3) regression analysis were considered. The regression parameters in all the three cases were calculated using the Least Square Method (LSM), using the daytime vertical E × B drift velocity and ΔH. A formula was developed which indicates the relationship between daytime vertical E × B drift velocity and ΔH, for the disturbed periods. The E × B drift velocity was then evaluated using the formulae thus found for the three regression analysis and validated for the ‘disturbed periods’ of 3 selected events. The E × B drift velocities estimated by the three regression analysis have a fairly good agreement with JULIA radar observed values under different seasons and solar activity conditions. Root Mean Square (RMS) errors calculated for each case suggest that polynomial (order 3) regression analysis provides a better agreement with the observations from among the three.