一种实用的计算热膨胀系数的递推方法

本文从热膨胀系数α、比热C_v 及体积弹性模量K 所满足的热力学关系出发,提出了一种简单实用的递推方法计算热膨胀系数,用此方法可以相当准确地计算固体热膨胀系数作为温度函数的整个曲线。文中以三种碱卤晶体为例计算了室温以下的热膨胀系数,与实验结果符合得非常好。     

The (s,Q) inventory model with Erlang lead time and deterministic demand

We develop a simple, approximately optimal solution to a model with Erlang lead time and deterministic demand. The method is robust to misspecification of the lead time and has good accuracy. We compare our approximate solution to the optimal for the case where we have prior information on the lead‐time distribution, and another where we have no information, except for computer‐generated sample data. It turns out that our solution is as easy as the EOQ's, with an accuracy rate of 99.41% when prior information on the lead‐time distribution is available and 97.54–99.09% when only computer‐generated sample information is available. Apart from supplying the inventory practitioner with an easy heuristic, we gain insights into the efficacy of stochastic lead time models and how these could be used to find the cost and a near‐optimal policy for the general model, where both demand rate and lead time are stochastic. © 2004 Wiley Periodicals, Inc. Naval Research Logistics, 2004     

Robust cubature Kalman filter method for the nonlinear alignment of SINS

Nonlinear initial alignment is a significant research topic for strapdown inertial navigation system(SINS).Cubature Kalman filter(CKF)is a popular tool for nonlinear initial alignment.Standard CKF assumes that the statics of the observation noise are pre-given before the filtering process.Therefore,any unpredicted outliers in observation noise will decrease the stability of the filter.In view of this problem,improved CKF method with robustness is proposed.Multiple fading factors are introduced to rescale the obser-vation noise covariance.Then the update stage of the filter can be autonomously tuned,and if there are outliers exist in the observations,the update should be less weighted.Under the Gaussian assumption of KF,the Mahalanobis distance of the innovation vector is supposed to be Chi-square distributed.Therefore a judging index based on Chi-square test is designed to detect the noise outliers,determining whether the fading tune are required.The proposed method is applied in the nonlinear alignment of SINS,and vehicle experiment proves the effective of the proposed method.     

车辆液力机械传动系统建模及动态特性仿真

建立了具有液力传动的履带车辆动力传动系统及整车的仿真模型,对车辆的加速性进行了仿真研究并与试验结果进行了比较,应用该仿真模型,分析了履带车辆换挡过程中发动机与涡轮转速、系统元件转速等的变化规律,结果表明该仿真模型能够方便的应用于车辆的性能分析与预测.     

基于PCA和BP神经网络的水下目标识别方法研究

针对被动声纳信号的特点,提出了基于信号线谱特征的主成分分析(PCA)特征选择方法,其优点是从复杂的目标信号中提取目标的特有信息,降低了目标特征维数.将此方法用于实录的三类水下目标数据,采用BP神经网络对目标进行识别分类,仿真结果说明了所提出的方法的正确性和有效性.     

如何在防化科研试验中加强安全保密工作

针对我院科研试验的特点和要求,分析了安全保密工作的艰巨性和重要性,明确了安全保密总要求,提出了把安全保密工作落到实处的具体措施。     

基于稀疏表示和非参数判别分析的降维算法

针对人脸识别问题提出一种新的监督降维算法。算法首先基于稀疏表示理论,利用同类样本间的稀疏重构来构建图。此方案不仅可以克服传统图构造方法中参数选择的困难,而且能够更好地刻画类内信息。然后,算法采用非参数类间离差来刻画类间信息,非参数类间离差在处理复杂分布数据时相比于参数类间离差更具判别力。最后,算法通过保持类内稀疏重构关系的同时最大化非参数类间离差来求得最优的投影矩阵。在ORL和Extended Yale B公共人脸数据库的实验表明,该算法能够获得较好的识别结果。     

舰船辐射噪声检测的被动合成孔径算法

舰船辐射噪声在低频段具有稳定的线谱成分,其特征信息丰富,利用该线谱成分可以实现对水下目标的检测.被动合成孔径(Passive Synthetic Aperture Sonar,PSAS)算法对小孔径基阵沿直线运动接收到的信号进行合成处理,从而达到虚拟大孔径基阵的方位分辨力效果,进而提高对弱目标信号的检测能力.理论分析结合仿真不同因素对被动合成孔径算法影响,验证了算法的有效性和可行性.     

基于锥形量热法的油池火相似性及点火特性模拟实验

针对油料池火灾相似性及点火特性研究需要,构建了一种基于耗氧原理的油池火锥形量热法模拟实验系统,引入火灾尺度相似性概念,研究了实验室尺度油池火与真实尺度油池火的相似性关系,探讨了实验室尺度油池火预测真实尺度油池火的可行性,基于实验室尺度锥形量热法研究了油池火点火特性,得到了辐射强度、辐射距离对油料点燃时间的影响规律以及点燃时间与锥照射强度之间的拟合公式。     

基于一般二元关系的不确定性度量方法研究

针对一般二元关系,从知识的区分能力角度提出一种带有可调节参数的新的不确定性度量-α熵,给出了其在一般二元关系下的重要性质,指出一般二元关系下的α熵是现有多种不确定性度量的扩展,统一了完备和不完备信息系统中知识的不确定性度量.结合知识的α熵,给出了一般二元关系下粗糙集的α精度和α粗糙度的定义,证明了α精度、α粗糙度和知识...