组合磁化用于增强铁磁材料脉冲涡流检测的灵敏度

脉冲涡流检测是近些年涌现出的一种新型无损检测技术。针对铁磁性材料的脉冲涡流检测,本文提出了一种组合磁化的方法。通过附加一个直流磁场对试件磁化,改变材料的磁导率,在加载脉冲激励时,可获得更高的检测灵敏度。理论分析和实验证明了组合磁化对检测灵敏度产生的影响。     

用灵敏度分析同步电液伺服系统误差

采用灵敏度方法来分析电液伺服系统中各参数变化对系统动态特性的影响，通过对参变量变动所引起的微分方程解变动的研究，可以分析系统精度受各参变量影响的大小。     

Transition prediction and sensitivity analysis for a natural laminar flow wing glove flight experiment

Natural laminar flow technology can significantly reduce aircraft aerodynamic drag and has excellent technical appeal for transport aircraft development with high aerodynamic efficiency. Accurately and efficiently predicting the laminar-to-turbulent transition and revealing the maintenance mechanism of laminar flow in a transport aircraft’s flight environment are significant for developing natural laminar flow wings. In this research, we carry out natural laminar flow flight experiments with different Reynolds numbers and angles of attack. The critical N-factor is calibrated as 9.0 using flight experimental data and linear stability theory from a statistical perspective, which makes sure that the relative error of transition location is within 5%. We then implement a simplified e^N transition prediction method with a similar accuracy compared with linear stability theory. We compute the sensitivity information for the simplified e^N method with an adjoint-based method, using the automatic differentiation technique (ADjoint). The impact of Reynolds numbers and pressure distributions on TS waves is analyzed using the sensitivity information. Through the sensitivity analysis, we find that: favorable pressure gradients not only suppress the development of TS waves but also decrease their sensitivity to Reynolds numbers; there exist three special regions which are very sensitive to the pressure distribution, and the sensitivity decreases as the local favorable pressure gradient increases. The proposed sensitivity analysis method enables robust natural laminar flow wings design.     

Adaptive modification of turbofan engine nonlinear model based on LSTM neural networks and hybrid optimization method

An accurate and reliable turbofan engine model which can describe its dynamic behavior within the full flight envelop and lifecycle plays a critical role in performance optimization, controller design and fault diagnosis. However, due to the performance differences caused by the tolerance of engine manufacturing and assembly, and performance degradation during continuously stringent environmental regulations, the model accuracy is severely reduced. In this paper, an adaptive modification method of turbofan engine nonlinear Component-Llevel Model (CLM) based on Long Short-Term Memory (LSTM) Neural Network (NN) and hybrid optimization algorithm is pro-posed. First, a dynamic compensator with a combined LSTM NN architecture is constructed to compensate for the initial error between the experimental data and CLM of a turbofan engine under health condition. Then, a sensitivity analysis approach based on the entropy coefficient and technique for order preference by similarity to an ideal solution integrated evaluation is developed to choose the unmeasurable health parameters to be adjusted. Finally, a parallel hybrid optimization algorithm is developed to complete the adaptive model modification when the performance degrades. The proposed method is verified on a military low-bypass twin-spool turbofan engine, and the experimental results show the effectiveness of the proposed method.     

Conceptual design,modeling and compliance characterization of a novel 2-DOF rotational pointing mechanism for fast steering mirror

In this paper, a novel 2-DOF rotational pointing mechanism(RPM) is designed inspired by the guidelines of the graphical approach. The mechanism integrates with a fast steering mirror(FSM) for compensating pointing errors of a laser beam. The design intends to achieve an angular travel of ±10 mrad and steers a 25 mm mirror aperture. A planar flexure with beam flexures accompanied in parallel with an axial flexure build-up mechanism configuration. Compliant mechanismbased RPM ensures high precisio...     

星载观测平台的视线误差分析

为分析星载观测平台各项误差源对视线测量精度的影响,研究了一种基于多参量的视线测量误差建模与评价方法.不同于以往卫星、相机的空间测量方式,针对卫星、转台、相机的观测结构,构建了从惯性空间到光学传感器像平面的目标成像模型及星载观测平台视线测量模型.通过推导星载观测平台视线测量误差与观测中13项误差源的关系,提出一种基于灵敏度分析的误差评价方法,并在三个轴向上分析了各项误差源对星载观测平台视线测量精度的影响.利用蒙特卡罗仿真试验验证了理论模型的有效性.结果表明,卫星轨道误差、卫星姿态误差、载荷平台角振动误差、内外框架转动误差、像平面目标像点的位置量化误差是影响星载观测平台视线测量精度的主要因素.该方法能够科学评估各项误差源对星载观测平台视线测量精度的影响,对星载观测平台的总体设计具有重要的应用价值.     

小天体动能撞击防御中动量传递因子敏感参数分析

动量传递因子 $ \beta $ 是评估动能撞击效果的重要参量。根据动能撞击过程中动量传递因子的理论模型,分析了撞击器特性参数和小天体结构特性参数对动量传递因子取值的影响,并对不同动能撞击方案以及不同材料特性小天体的成坑效应和动量传递因子进行分析。研究表明：标度律参数 $ \mu $ 对 $ \beta $ 影响较大, $ \mu $ 是地面实验拟合得到的系数,与材料强度特性相关;当小天体为单体岩石结构时,撞击器速度及密度、小天体密度及表面强度对 $ \beta $ 影响较大,而撞击器半径和小天体引力对 $ \beta $ 影响较小;当小天体为碎石堆结构时, $ \beta $ 对撞击器特性参数和小天体特性参数不敏感,且数值较小。对三种不同动能撞击方案的成坑效应与动量传递因子形成规律进行研究,发现撞击器初始动能对 $ \beta $ 影响较大。当小天体为单体岩石结构时,其对应的动量传递因子取值较大,而当小天体为碎石堆结构时,其对应的 $ \beta $ 取值较小且基本不变。对相同动能撞击方案下不同材料特性小天体（C型、S型和X型小行星）产生的撞击效应进行分析,发现在引力主导时,βC>βS >βX,而在强度主导时 $ \beta $ 取值较小且基本相同。     

Quantification of parametric uncertainty in γ-Reθ model for typical flat plate and airfoil transitional flows

Owing to the lack of physical knowledge of boundary layer transition, the γ-Re_θ transition model introduces closure parameters, which increase the uncertainty of transition prediction. The objective of this work is to quantify the uncertainties of closure parameters in the quantities of interests and identify the key parameters. The six closure parameters in the uncertainty intervals are used as input variables, and the uncertainties of the output results are propagated by a stochastic expansion based on the point-collocation nonintrusive polynomial chaos method. The relative contribution of each parameter to uncertainty is evaluated by the Sobol index. The computational cases include natural and bypass transitional flows on zero-pressure-gradient flat plates, and subsonic and transonic flows around airfoils. For most cases, c_e2, c_a2, and c_a1 dominate the uncertainty, and the influence of σ_θt is also significant when the history effects of flow are evident. The contribution of parameters in airfoils is more complex than that in flat plates. The transonic airfoil case shows that flow separation dramatically changes the distribution of Sobol indices, which poses a challenge to the accurate prediction of transition. Generally, c_e2 and c_a2 are the key parameters of the γ-Re_θ model.     

基于LEO辅助的北斗B1C高灵敏快速捕获算法

随着低轨(LEO)卫星数量的不断增加,利用LEO星座辅助增强GNSS导航性能已经成为一种新的趋势.针对低信噪比环境下B1C信号难以捕获的问题,提出了一种基于LEO辅助的B1C信号高灵敏快速捕获算法.首先对提升接收机捕获灵敏度进行了分析,对比了相干积分与非相干积分对于信号处理增益的影响,得出在低轨导航增强信号的辅助下采用增加相干积分时间的捕获算法对低信噪比条件下B1C信号的捕获更有效.然后提出了一种基于LEO辅助的B1C高灵敏快速捕获算法,从理论分析和实验仿真两方面,对比验证了在LEO辅助下可以显著提高B1C信号的捕获灵敏度,缩短捕获时间,提高捕获效率.     

MEMS“三明治”倾角传感器的仿真分析和优化设计

对MEMS“三明治”式倾角传感器进行结构优化设计，敏感元件采用双梁-质量块结构，其中可动质量块通过双梁和周围框架相连，可动质量块和上下盖板构成上下差分电容。外界给定某一加速度时，上下间隙此消彼长，从而导致电容量发生变化。通过建立敏感元件的静力学模型，获得敏感元件的关键尺寸与其性能参数的关系，基于体硅工艺建立敏感元件的三维工艺模型，并采用ANSYS有限元仿真对敏感元件的灵敏度、线性度、谐振频率等参数进行分析计算，结果表明：敏感结构的一阶谐振频率为576.68 Hz，灵敏度为0.76 pF/g，±30°、±90°对应的线性度分别为0.8‰、3‰，均符合设计要求，最后给出了倾角传感器敏感元件的加工流程。