装甲车辆动力传动系统整体性工程初探

全面考虑装甲车辆动力传动系统论证、研制、生产及使用等方面的因素,从整体、系统和全局的观点出发,论述了装甲车辆动力传动系统的整体式设计、一体化控制、性能综合评价和寿命周期费用分析.从而把装甲车辆动力传动系统的论证、研制、生产及使用看作一个整体性工程来考虑,克服了以往设计和使用中重点突出某一过程或部件,而忽略相互匹配和顾此失彼的问题,为在现有技术基础上进一步提高装甲车辆的机动性能,提供了一种新的研究思路.     

高原卫士奉献精神的哲学反思

立足推进人类社会精神文明建设和加强部队思想建设,把高原卫士作为认识对象,运用马克思认识论和实践观,分析高原卫士在特殊环境里所具备的那种高尚品格和生命价值观。在阐述高原卫士奉献精神本质、内涵,及其实践效果的基础上,追问奉献精神产生的双重根源,指出:高原卫士可贵之处是奉献,人类文明需要可贵的奉献精神。     

JTIDS系统扩频码的优选及扩频图案的设计

首先介绍了联合战术信息分发系统(JTIDS)的一般概念,进而针对它的抗干扰措施———直接序列扩频的扩频码的优选及扩频图案的设计,提出了合适的算法,并用C语言在微机上仿真实现。实验结果证明优选的码字质量高,生成速度快,此方面的仿真实现逼近JTIDS,有利于对JTIDS进行深入研究,从而对它实施有效干扰。     

设备管理系统的排队论分析

该文应用排队论的理论分析了设备损修系统中最优设备的解法。     

基于时频分布的弹道导弹目标识别方法

在弹道导弹目标识别中,微动特征是重要的识别手段。从弹道导弹微动特性时频分析出发,提出一种基于时频分布的弹道导弹目标识别方法。该方法将时频分布图的伪Zeinike不变矩特征作为识别特征。首先对回波信号进行时频变换以获取时频图像;然后为了降低噪声的影响,对其进行图形预处理;最后给出了伪Zernike不变矩提取步骤及识别特征的选取原则。通过仿真实验,分析了不同特征组合对识别率的影响,评估了不同信噪比下识别方法的稳定性。实验结果表明,该方法具有一定稳定性,可用于弹道导弹目标识别。     

基于Bayes统计理论的射表编拟方法

全面系统阐述了Bayes统计理论下的射表编拟方法,具体研究了验前信息的处理、符合计算、编拟计算及试验用弹量的确定等几个关键难点问题,同时导出了确定先验分布中未知参数的计算公式、射表基本诸元的后验估计公式、射表试验用弹量的计算公式。通过两个实例对其具体使用方法给予了详细说明并对其结果进行了分析,指出应用该方法可以在相同精度要求下节省用弹量或在相同用弹量下提高射表精度,具有很好的经济适用价值。     

基于改进支持向量回归机的火炮身管寿命预测

为准确预测火炮身管寿命终止时火炮射弹数,根据射击过程中火炮身管磨损量与身管寿命特性,分析了身管膛线起始部磨损量与身管射弹数之间的关系,提出了支持向量回归机算法,并采用遗传算法进行模型优化改进,得到火炮身管寿命预测最优模型。结合两种类型火炮的身管数据,利用该模型对身管寿命进行预测,并与原始支持向量回归机进行对比,通过分析可知改进的支持向量回归机预测效果好、精度高,为火炮在实际应用中身管的寿命预测提供了新的思路。     

Scheduling a production–distribution system to optimize the tradeoff between delivery tardiness and distribution cost

We consider a make‐to‐order production–distribution system with one supplier and one or more customers. A set of orders with due dates needs to be processed by the supplier and delivered to the customers upon completion. The supplier can process one order at a time without preemption. Each customer is at a distinct location and only orders from the same customer can be batched together for delivery. Each delivery shipment has a capacity limit and incurs a distribution cost. The problem is to find a joint schedule of order processing at the supplier and order delivery from the supplier to the customers that optimizes an objective function involving the maximum delivery tardiness and the total distribution cost. We first study the solvability of various cases of the problem by either providing an efficient algorithm or proving the intractability of the problem. We then develop a fast heuristic for the general problem. We show that the heuristic is asymptotically optimal as the number of orders goes to infinity. We also evaluate the performance of the heuristic computationally by using lower bounds obtained by a column generation approach. Our results indicate that the heuristic is capable of generating near optimal solutions quickly. Finally, we study the value of production–distribution integration by comparing our integrated approach with two sequential approaches where scheduling decisions for order processing are made first, followed by order delivery decisions, with no or only partial integration of the two decisions. We show that in many cases, the integrated approach performs significantly better than the sequential approaches. © 2005 Wiley Periodicals, Inc. Naval Research Logistics, 2005     

A model to predict the residual life of aircraft engines based upon oil analysis data

This paper reports on a study using the available oil monitoring information, such as the data obtained using the Spectrometric Oil Analysis Programme (SOAP), to predict the residual life of a set of aircraft engines. The relationship between oil monitoring information and the residual life is established using the concept of the proportional residual, which states that the predicted residual life may be proportional to the wear increment measured by the oil analysis programmes. Assuming such a relationship between wear and the residual life exists, we formulated a recursive prediction model for the item's residual life given measured oil monitoring information to date. A set of censored life data of 30 aircraft engines (right censored due to preventive overhaul) along with the history of their monitored metal concentration information are available to us. The metal concentration information includes many variables, such as Fe, Cu, Al, etc.; not all of them are useful, and some of them may be correlated. The principal component analysis (PCA) has been adopted to reduce the dimension of the original data set and to produce a new set of uncorrelated variables, which we shall use in the prediction model. The procedure associated with estimating model parameters is discussed. The model is fitted to the actual SOAP data from the aircraft engines, and the goodness‐of‐fit test has been carried out. © 2005 Wiley Periodicals, Inc. Naval Research Logistics, 2005.     

基于退化速率跟踪粒子滤波的剩余使用寿命预测框架

毋庸置疑,剩余使用寿命预测对于设备的健康管理越来越重要。近年来粒子滤波方法被越来越多地应用到设备寿命预测技术当中,这是因为粒子滤波方法能更好的解决非线性非高斯系统滤波问题,而且能够获得不确定度信息。但该方法的预测性能却过度依赖于预测模型,并且对于模型参数的初始分布也比较敏感,这在一定程度上限制了粒子滤波预测方法的进一步发展。本文针对基本粒子滤波预测方法的不足,提出了一种基于退化速率跟踪粒子滤波的通用预测框架,以历史观测数据的退化速率统计规律作为指导来跟踪目标数据的退化速率,实现对粒子滤波预测方法的简化。并将该方法用于轴承和锂离子电池的剩余使用寿命预测,验证了方法的有效性。