发动机振动诊断及振源分析法

近几年来,现役某小型战斗机已有十多架次因飞行员反映空中振动大而停飞。由于没有空测手段,无法作出确切判断,致使有的飞机停飞长达一年之久,直接影响部队飞行训练。为此,研制了“机载振动数据采集系统”及“地面分析设备”和提出了空中振动大的故障诊断及振源分析方法与诊断程序。(1)为研究解决空中振动大的故障提供检测手段、定量数据和分析方法;(2)为处理因反映空中振动大而停飞问题提供科学依据;(3)对保证飞行安全和提高飞机良好率有直接作用;(4)可推广到其它现役机种的振动监控和振动诊断,也可应用于新机试飞,以便评定空中振动品质。      

RCD太阳帆航天器人工平动点轨道保持与控制

针对航天器平动点轨道保持问题,研究了含有反射率控制设备(RCD)的太阳帆航天器在日地系共线人工平动点处的轨道保持与控制,同时降低因频繁改变航天器姿态所带来的振动问题。首先,基于太阳帆圆型限制性三体问题,计算了RCD型太阳帆人工平动点位置,给出了太阳帆共线人工平动点三阶Halo轨道,并将其作为参考轨道;然后,将太阳帆动力学方程线性化,采用跟踪控制输出的方法对线性模型进行控制;最后,通过合理选择控制变量矩阵,将控制律代入非线性模型中进行轨道保持控制。仿真结果表明,通过控制RCD太阳帆反射率设备参数及姿态角,实现了长时间的Halo轨道保持,同时大幅减小了太阳帆姿态角的改变,从而减小了帆面振动,为太阳帆航天器长期轨道任务的实现提供了良好的理论依据。     

升力体式密闭救生舱无控制再入研究

将救生舱选定为升力体模型,利用数值模拟的方法动态研究救生舱再入过程中的稳定性和减速性,分析无主动控制的救生舱返回的可行性。针对高超声速和马赫数小于4两种工况,分别采用牛顿理论方法和CFD方法进行气动力计算;利用气动特性计算结果求解六自由度轨道仿真动力学方程进行轨迹计算。研究结果显示,救生舱初始再入条件合适时,其再入过程具有稳定性;仅依靠目前救生舱外形的结构减速不能满足减速性要求,需辅助其他减速措施。     

民用飞机刹车控制系统软件构型管理研究

民用飞机刹车控制系统构型管理在系统设计开发过程和适航符合性验证过程中发挥着关键作用。为了提升民用飞机刹车控制系统软件构型管理能力,使该系统设计开发的软件满足适航要求,介绍刹车控制系统软件构型管理的概念和方法,描述如何运用系统思维和信息化流程手段将构型管理和软件设计相结合,开展软件全生命周期过程构型管理活动。结合DO-178C 的要求,提出建立以产品构型为核心的构型数据数字化管理机制,实现刹车控制系统软件研制的单一数据源。结果表明：通过和构型基线管理相结合建立一个统一的构型数据库,在构型库中严格按照阶段的状态进行准确记录,确保了状态信息的实时性、可追溯性、完整性及有效性,达到了最终构型控制目标,可以满足适航要求。     

基于FPGA IP核的脉冲压缩算法的实现

线性调频脉冲压缩信号具有作用距离远、抗干扰能力强的特点。为实现线性调频信号的数字脉冲压缩,文章提出了一种基于FPGA IP核的脉冲压缩设计方法。文章着重介绍了如何使用FPGA IP核来实现频域脉冲压缩,同时对使用流水线型或基2结构实现FFT算法的优缺点和适应性做了详细对比。实验结果表明,文章提出的脉冲压缩设计方法性能良好,便于工程实现。且该方法的参数设置灵活,可以简化FPGA软件设计,缩短研发周期。     

二维Euler方程的自适应网格矢通量算法

给出了二维轴对称欧拉方程的自适应网格隐式矢通量分裂差分格式和模拟结果,隐式矢通量分裂格式不需人工粘性项与人工耗散项,可以计算跨声速流场,也可以较准确地捕获激波,利用流场解的梯度信息对网格进行调整,可以提高激波的捕获精度,算例表明,该方法精度高稳定性好,不依赖于初始条件。     

压电薄板的建模和阻尼的准独立模态控制

导出压电薄板的传递函数模型,建立起压电结构与一般结构模态控制的类比关系。基于此,结合实验研究,提出“准独立模态控制”方法,能在尽可能简单的硬件条件下逼近独立模态控制目标。多模态阻尼控制实验进程和结果表明了它的有效性和实用性。     

Study on segmented distribution for reliability evaluation

In practice, the failure rate of most equipment exhibits different tendencies at different stages and even its failure rate curve behaves a multimodal trace during its life cycle. As a result, traditionally evaluating the reliability of equipment with a single model may lead to severer errors. However, if lifetime is divided into several different intervals according to the characteristics of its failure rate, piecewise fitting can more accurately approximate the failure rate of equipment. There-fore, in this paper, failure rate is regarded as a piecewise function, and two kinds of segmented dis-tribution are put forward to evaluate reliability. In order to estimate parameters in the segmented reliability function, Bayesian estimation and maximum likelihood estimation (MLE) of the seg-mented distribution are discussed in this paper. Since traditional information criterion is not suit-able for the segmented distribution, an improved information criterion is proposed to test and evaluate the segmented reliability model in this paper. After a great deal of testing and verification, the segmented reliability model and its estimation methods presented in this paper are proven more efficient and accurate than the traditional non-segmented single model, especially when the change of the failure rate is time-phased or multimodal. The significant performance of the segmented reli-ability model in evaluating reliability of proximity sensors of leading-edge flap in civil aircraft indi-cates that the segmented distribution and its estimation method in this paper could be useful and accurate.     

Multi-EAP:Extended EAP for multi-estimate extraction for SMC-PHD filter

The ability to extract state-estimates for each target of a multi-target posterior, referred to as multi-estimate extraction (MEE), is an essential requirement for a multi-target filter, whose key performance assessments are based on accuracy, computational efficiency and reliability. The probability hypothesis density (PHD) filter, implemented by the sequential Monte Carlo approach, affords a computationally efficient solution to general multi-target filtering for a time-varying num-ber of targets, but leaves no clue for optimal MEE. In this paper, new data association techniques are proposed to distinguish real measurements of targets from clutter, as well as to associate par-ticles with measurements. The MEE problem is then formulated as a family of parallel single-estimate extraction problems, facilitating the use of the classic expected a posteriori (EAP) estima-tor, namely the multi-EAP (MEAP) estimator. The resulting MEAP estimator is free of iterative clustering computation, computes quickly and yields accurate and reliable estimates. Typical sim-ulation scenarios are employed to demonstrate the superiority of the MEAP estimator over existing methods in terms of faster processing speed and better estimation accuracy.     

基于图像特征分类和RBF网络的两轴车辆动态称重技术

汽车在行驶过程中的总重信号通常由各轴重信号确定,各轴重信号的测试精度取决于对车辆运动参数和振动信号等的精确分析。本文采用径向基函数(Radial basis function,RBF)网络处理轴重信号,针对该网络的泛化能力与拟合精度的矛盾,将车辆按照重量分为大、中、小3种类型,并进行整车建模和网络训练;实际测试过程中,利用汽车俯视图像提取类型特征,然后根据汽车的类型将测试参数输入不同的神经网络进行处理,以静态测量结果为相对真值。仿真结果表明,分类建模比单一混合建模具有更高的测试精度。