基于战备完好率的军用飞机维修费用需求确定方法

军用飞机维修费用需求与战备完好率要求密切相关,为保持飞机一定的战备完好率水平,必须投入一定的维修费用。维修费用投入多,则维修设备齐全,维修人员维修能力高,维修备件充足,飞机故障修复时间短,战备完好率高;维修费用投入少,会造成维修设备短缺,设施破旧,维修人员培训不到位,维修备件供应不足等各种问题,直接影响战备完好率水平。     

相位差变化率的快速高精度测量及精度分析

由于阵元间相位差变化率这一观测量与通道不一致性关系不大,信号到达两阵元间的相位差变化率常用于无源定位测量中。提出了一种新的快速高精度的相位差变化率测量方法,利用分时间片思想,首先通过对无模糊相位差进行一次相位平移,得到各个时间片含模糊的相位差值;然后对得到的各个时间片的含模糊相位差进行一次相位平移,得到各时间片间相对无模糊的相位差;最后对相对无模糊相位差采用最小二乘算法求得相位差变化率。理论分析和仿真实验表明,本算法可以很好地解决测量中由于相位模糊造成的相位差抖动问题,能够在短时间内得到高精度相位差变化率信息,可以满足定位要求。     

基于FPGA的可变速率PSK数字解调器实现

针对QPSK变速率调制数字系统,提出了一种新的基于现场可编程门阵列(FPGA)实现方法,该系统可以支持4.88 Kb/s到2 Mb/s和更高的连续比特速率。设计采用混合乘法器、数控振荡器(NCO)和积分-梳状滤波器(CIC),并给出了系统中载波和信号恢复电路的设计结构,且可以移植到任何FPGA器件。提出的设计在Xilinx Virtex-5 FPGA平台进行了硬件测试。硬件实现结果显示,采用本方法实现的解调器,表现出优越的使用效率。     

管壳式换热器强制对流换热与阻力特性研究

用实验与软件模拟相结合的方法研究了波纹管与直管的换热性能和阻力特性.壳程采用通入高温烟气,测试了不同水量情况下波纹管的平均对流换热系数和阻力系数,拟合出了所测参数范围内的换热和阻力关联式,并比较了相同管径的波纹管与直管的换热效果.为波纹管在换热领域的应用提供一些依据.     

高空动能拦截器末制导导引方法设计与实现

以高空动能拦截器为研究对象,为其末制导段设计了一种“逐段限制视线转率”的导引方法,使之最终能直接命中目标,实现动能拦截的任务并通过仿真计算验证了该导引法的可行性。     

Response surface analysis of two‐stage stochastic linear programming with recourse

We apply the techniques of response surface methodology (RSM) to approximate the objective function of a two‐stage stochastic linear program with recourse. In particular, the objective function is estimated, in the region of optimality, by a quadratic function of the first‐stage decision variables. The resulting response surface can provide valuable modeling insight, such as directions of minimum and maximum sensitivity to changes in the first‐stage variables. Latin hypercube (LH) sampling is applied to reduce the variance of the recourse function point estimates that are used to construct the response surface. Empirical results show the value of the LH method by comparing it with strategies based on independent random numbers, common random numbers, and the Schruben‐Margolin assignment rule. In addition, variance reduction with LH sampling can be guaranteed for an important class of two‐stage problems which includes the classical capacity expansion model. © 1999 John Wiley & Sons, Inc. Naval Research Logistics 46: 753–776, 1999     

长码直扩信号的符号速率盲估计方法

针对长码直接序列扩频(DSSS)信号的符号速率估计的难题,提出了基于相关处理的方法。该方法首先估计长码直扩信号的相关函数二阶矩,然后将相关函数二阶矩的估计作为输入信号进行预处理,以去除扩频码周期处的峰值。对预处理后的信号再次进行自相关处理,则所得的信号的频谱中含有符号速率谱线。理论分析和计算机仿真证明了所提出的算法的有效性。     

A novel noise reduction technique for underwater acoustic signals based on complete ensemble empirical mode decomposition with adaptive noise,minimum mean square variance criterion and least mean square adaptive filter

Underwater acoustic signal processing is one of the research hotspots in underwater acoustics. Noise reduction of underwater acoustic signals is the key to underwater acoustic signal processing. Owing to the complexity of marine environment and the particularity of underwater acoustic channel, noise reduction of underwater acoustic signals has always been a difficult challenge in the field of underwater acoustic signal processing. In order to solve the dilemma, we proposed a novel noise reduction technique for underwater acoustic signals based on complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN), minimum mean square variance criterion (MMSVC) and least mean square adaptive filter (LMSAF). This noise reduction technique, named CEEMDAN-MMSVC-LMSAF, has three main advantages: (i) as an improved algorithm of empirical mode decomposition (EMD) and ensemble EMD (EEMD), CEEMDAN can better suppress mode mixing, and can avoid selecting the number of decomposition in variational mode decomposition (VMD); (ii) MMSVC can identify noisy intrinsic mode function (IMF), and can avoid selecting thresholds of different permutation entropies; (iii) for noise reduction of noisy IMFs, LMSAF overcomes the selection of decomposition number and basis function for wavelet noise reduction. Firstly, CEEMDAN decomposes the original signal into IMFs, which can be divided into noisy IMFs and real IMFs. Then, MMSVC and LMSAF are used to detect identify noisy IMFs and remove noise components from noisy IMFs. Finally, both denoised noisy IMFs and real IMFs are reconstructed and the final denoised signal is obtained. Compared with other noise reduction techniques, the validity of CEEMDAN-MMSVC-LMSAF can be proved by the analysis of simulation signals and real underwater acoustic signals, which has the better noise reduction effect and has practical application value. CEEMDAN-MMSVC-LMSAF also provides a reliable basis for the detection, feature extraction, classification and recognition of underwater acoustic signals.     

大规模科学数据体绘制技术综述

体绘制是刻画大规模科学数据中复杂物理特征的有效途径,然而,数据量极大、特征难以捕捉等问题依然是目前体绘制研究的主要挑战。为此,研究者们从三个方面对体绘制算法进行了深入研究,以提高大规模数据体绘制的效率和效果。一方面,依托硬件通过多处理器核来分担计算,降低单处理器核所要完成的计算量,是提高体绘制效率的一个有效途径。另一方面,充分发掘数据场内在特性对三维数据场进行约简,大幅减少绘制处理数据量从而降低算法开销,也是提高体绘制效率的一个有效途径。同时,在体绘制算法中融入特征分析和特征增强方法,让复杂物理特征从数据场中突显出来,以实现对科学数据的高质量绘制。本文对国内外体绘制技术相关研究进展进行了调研、综述,并分析了不同的研究方法,最后展望了未来体绘制技术研究的可能发展方向,包括应用驱动的特征体绘制、基于特征的约简体绘制、适应硬件的体绘制多级加速以及原位智能化体绘制等。     

Adaptive importance sampling for extreme quantile estimation with stochastic black box computer models

Quantile is an important quantity in reliability analysis, as it is related to the resistance level for defining failure events. This study develops a computationally efficient sampling method for estimating extreme quantiles using stochastic black box computer models. Importance sampling has been widely employed as a powerful variance reduction technique to reduce estimation uncertainty and improve computational efficiency in many reliability studies. However, when applied to quantile estimation, importance sampling faces challenges, because a good choice of the importance sampling density relies on information about the unknown quantile. We propose an adaptive method that refines the importance sampling density parameter toward the unknown target quantile value along the iterations. The proposed adaptive scheme allows us to use the simulation outcomes obtained in previous iterations for steering the simulation process to focus on important input areas. We prove some convergence properties of the proposed method and show that our approach can achieve variance reduction over crude Monte Carlo sampling. We demonstrate its estimation efficiency through numerical examples and wind turbine case study.