液体火箭发动机环境因子的Bayes估计

基于液体火箭发动机的寿命服从威布尔分布的条件,假定天地试验环境下威布尔分布的形状参数不变,运用Bayes方法对weibull分布天地实验条件下的环境因子进行分析,给出了环境因子在平方损失下的Bayes估计,并与极大似然估计法进行比较,通过仿真实例验证了该方法的有效性。     

航天器环境干扰力矩的闭环辨识与补偿

研究引入干扰力矩辨识的方法提高三轴稳定航天器在稳态运行期间的高精度指向控制问题.基于航天器的稳态输出数据和系统传递函数,对环境干扰力矩的完整模型进行闭环辨识.其中采用改进的特征系统实现相关算法和多元线性回归法辨识环境干扰力矩的模型参数,最后使用前馈控制对所辨识的环境干扰力矩实现在线补偿.分析和仿真结果表明,该方案能有效地克服不确定的环境干扰力矩对姿态稳定度的影响,提高在轨运行航天器的姿态稳定精度.     

现代民机新型灭火剂性能研究

对新型灭火剂研究背景和种类进行了简要介绍,对具有开发潜力的新型灭火剂的理化性能、毒性、腐蚀性、灭火性能、环保性能进行深入分析与研究。通过对新型灭火剂性能的研究,得出每种灭火剂的优缺点,筛选出适用于现代民机灭火系统的灭火剂。     

Global Environmental Alert Service (GEAS)

Early warning systems represent an innovative and effective approach to mitigate the risk associated with natural hazards. Early warning technologies are now available for almost all natural hazards and systems are already in operation in all parts of the world. Nevertheless, recent disasters such as the Indian Ocean tsunami in 2004 and Katrina hurricane in 2005, highlighted inadequacies in early warning technologies.

Efforts towards the development of a global warning system are necessary for turning the tide in early warning processes and technologies. There is a pressing need for a globally comprehensive early warning system based on existing systems. The global system should be a mechanism which can consolidate scientific information and evidences, package this knowledge in a form usable to international and national decision makers and actively disseminate this information to those users.

The proposed Global Environmental Alert Service (GEAS) will provide information emanating from monitoring, Earth observing and early warning systems to users in a near-real-time mode and bridge the gap between the scientific community and policy makers. Characteristics and operational aspects of such a service, GEAS, are discussed.     

CAI课件的创作策略与使用体会

本文结合自己开发和使用《微机应用基础》多媒体教学课件实践过程，简单阐述了几点CAI课件创作的一般策略和使用体会。     

论航天器的环境试验和可靠性

讨论了航天器环境试验在提高航天器可靠性中所起的作用,环境试验和可靠性试验之间的关系;介绍了国外航天器环境试验的要求及应用情况;并对如何更好地发挥环境试验的作用提出一些建议。     

液体火箭发动机环境因子的修正逆矩估计

对文献 [1]提出的适用于大样本失效数据的逆矩估计法进行修正 ,针对液体火箭发动机飞行及地面试车数据的特点 ,提出了其天地环境因子的修正逆矩估计方法。与现有方法相比 ,本文提出的方法更加适用于小样本失效数据情形下环境因子问题的研究。最后用数值例说明了该方法的应用     

面向建筑空间的OFDM信号定位性能分析

针对利用OFDM信号进行定位时信号非连续性问题,提出一种粗检测和精细检测结合的测距方法,将距离测量转换为不同尺度的时延样点,采用时域粗检测快速估算接收OFDM信号的最大相关峰值,然后对传输时延进行频域精细测量,提升了小数倍采样周期时延测量的精度。在此基础上,分析了OFDM信号的定位性能,仿真结果表明,当OFDM信号在信噪比-11dB的情况下测距误差由3m左右(子载波数512)降至1m(子载波数4096)。     

基于蓝牙4.0的接近度分类室内定位算法

蓝牙4.0技术已经广泛应用于手机、平板电脑等移动终端设备,使得利用其实现室内定位具有极其广阔的应用前景。通过对蓝牙4.0技术的研究,根据蓝牙4.0 RSSI损耗特征进行接近度分类,提出一种限定区域k-近邻改进算法。实验结果表明,运用优化后的RSSI指纹定位算法室内定位平均误差可达到dm级,可充分满足商用室内LBS“m级”的定位精度和“s级”响应的需求。     

Environmental stress level evaluation approach based on physical model and interval grey association degree

 Associating environmental stresses (ESs) with built-in test (BIT) output is an important means to help diagnose intermittent faults (IFs). Aiming at low efficiency in association of traditional time stress measurement device (TSMD), an association model is built. Thereafter, a novel approach is given to evaluate the integrated environmental stress (IES) level. Firstly, the selection principle and approach of main environmental stresses (MESs) and key characteristic parameters (KCPs) are presented based on fault mode, mechanism, and ESs analysis (FMMEA). Secondly, reference stress events (RSEs) are constructed by dividing IES into three stress levels according to its impact on faults; and then the association model between integrated environmental stress event (IESE) and BIT output is built. Thirdly, an interval grey association approach to evaluate IES level is proposed due to the interval number of IES value. Consequently, the association output can be obtained as well. Finally, a case study is presented to demonstrate the proposed approach. Results show the proposed model and approach are effective and feasible. This approach can be used to guide ESs measure, record, and association. It is well suited for on-line assistant diagnosis of faults, especially IFs.