自由飘浮空间机器人准刚性分解运动轨迹控制与仿真

研究轨道空间机器人操作时,基座处于自由飘浮状态的手爪准刚性运动直角坐标轨迹的分解运动控制,重点分析了广义雅可比矩阵的计算,并进行了空间单手３—ＤＯＦ的仿真,该方法可相应推广到开链多手。     

阶比谱分析与汽车起动电机故障的实时诊断

本文主要论述阶比谱分析方法及其在汽车起动电机故障实时诊断中的应用。首先阐述了阶比谱分析的原理以及阶比采样中混迭与泄漏的产生及其抑制方法,然后讨论了如何在起动电机运行过程短、升速快的情况下获取感兴趣的噪声信号,进而采用阶比谱分析方法从信号中提取故障特征信息,最后利用阀值判别法起动电机的故障进行实时诊断。     

Force chains based mesoscale simulation on the dynamic response of Al-PTFE granular composites

Force chains based mesoscale simulation is conducted to investigate the response behavior of aluminum-polytetrafluoroethylene (Al-PTFE) granular composites under a low-velocity impact. A two-dimensional model followed the randomly normal distribution of real Al particles size is developed. The dynamic compressive process of Al-PTFE composites with varied Al mass fraction is simulated and validated against the experiments. The results indicate that, force chains behavior governed by the number and the size of agglomerated Al particles, significantly affects the impact response of the material. The failure mode of the material evolves from shear failure of matrix to debonding failure of particles with increasing density. A high crack area of the material is critical mechanism to arouse the initiation re-action. The damage maintained by force chains during large plastic strain builds up more local stresses concentration to enhance a possible reaction performance. In addition, simulation is performed with identical mass fraction but various Al size distribution to explore the effects of size centralization and dispersion on the mechanical properties of materials. It is found that smaller sized Al particle of com-posites are more preferred than its bulky material in ultimate strength. Increasing dispersed degree is facilitated to create stable force chains in samples with comparable particle number. The simulation studies provide further insights into the plastic deformation, failure mechanism, and possible energy release capacity for Al-PTFE composites, which is helpful for further design and application of reactive materials.     

加强军队全面建设是党执政的一项重大战略任务--学习《中共中央关于加强党的执政能力建设的决定》

<中共中央关于加强党的执政能力建设的决定>指出,坚持国防建设与经济建设协调发展,建设一支现代化、正规化的革命军队,是党执政的一项重大战略任务.坚持党对军队的绝对领导,加强军队全面建设,既是对我们党取得执政经验的科学总结,又是巩固我们党执政地位的现实保障,同时,加强军队全面建设对提高我们党的执政能力还具有服务和促进的功能.     

基于专家系统的防化保障预案评估研究

人工智能技术在众多领域获得广泛应用．为满足现代战争对防化指挥手段的现代化要求,针对不易量化的防化指挥决策问题的评估,提出了构建知识库并应用模糊推理机制建立专家系统,据此进行防化保障预案的评估选优方法,并对该方法的求解过程进行了探讨．     

军队现代化建设必须以人为本

以人为本是科学发展观的核心,也是指导各项工作的世界观与方法论的集中体现。军队现代化建设坚持以人为本,有着三个相互联系的方面:一是以人为本需要正确处理人和武器的关系,在二者的辩证统一中加强军队现代化建设,是我们必须确立的科学建设理念;二是以人为本只有在军人特别是军官的素质与能力转化中才能得到凸显,这是贯彻以人为本重要的实践原则;三是以人为本还要正确把握军人个人利益与人民利益的联结,自觉无私奉献,坚守革命军人“全心全意为人民服务”的伟大价值取向。     

机载预警雷达对海上悬停直升机的探测

提出了依托机载预警(AEW)雷达利用悬停直升机旋翼回波信号来探测海上悬停直升机目标的方案．着重就机载预警雷达采用时－空级联自适应处理技术对海杂波的抑制和旋翼回波信号处理的方法进行了研究．最后,给出了计算机仿真结果．     

基于 AR 模型和SPRT 检验法的过程状态监测

本文利用自适应卡尔曼滤波器原理建立机械系统过程监测模型—AR模型,并根据AR模型系数的变化可以表征系统过程状态这一特点,通过序贯概率比(SPRT)这一假设检验法,对机械系统的运行状况进行判别。实验表明,该方法行之有效,最后,本文给出了实验结果。     

A Markovian model for process setup and improvement

We examine the setup and improvement policies for a production process with multiple performance states. Assume that the production process deteriorates randomly over time, following a Markovian process with known transition probabilities. In order to reduce the production cost incurred because of process deterioration, the process is inspected at the end of each period. Then one of three actions may be taken: do nothing, perform routine process setup, or perform routine setup and process improvement. The routine setup operation returns the process to its best performance state, whereas the process improvement action may reduce future production and setup costs and improve the process-state transition probabilities. A discounted Markovian model is formulated to find the strategy that minimizes the total cost of operating the production process. © 1997 John Wiley & Sons, Inc. Naval Research Logistics 44: 383–400, 1997     

Exact bayesian estimation of system reliability from component test data

System reliability is often estimated by the use of components' reliability test results when system test data are not available, or are very scarce. A method is proposed for computing the exact posterior probability density function, cumulative distribution function, and credible intervals for system reliability in a Bayesian setting, with the use of components' prior probability distributions and current test results. The method can be applied to series, parallel, and many mixed systems. Although in theory the method involves evaluating infinite series, numerical results show that a small number of terms from the infinite series are sufficient in practice to provide accurate estimates of system reliability. Furthermore, because the coefficients in the series follow some recurrence relations, our results allow us to calculate the reliability distribution of a large system from that of its subsystems. Error bounds associated with the proposed method are also given. Numerical comparisons with other existing approaches show that the proposed method is efficient and accurate. © 1997 John Wiley & Sons, Inc.