Data association based on target signal classification information

In most of the passive tracking systems, only the target kinematical information is used in the measurement-to-track association, which results in error tracking in a multitarget environment, where the targets are too close to each other. To enhance the tracking accuracy, the target signal classification information （TSCI） should be used to improve the data association. The TSCI is integrated in the data association process using the JPDA （joint probabilistic data association）. The use of the TSCI in the data association can improve discrimination by yielding a purer track and preserving continuity. To verify the validity of the application of TSCI, two simulation experiments are done on an air target-tracing problem, that is, one using the TSCI and the other not using the TSCI. The final comparison shows that the use of the TSCI can effectively improve tracking accuracy.     

永磁同步电动机电磁振动特性及抑制措施

电磁振动水平是永磁同步电动机的重要评价指标之一,为了有效抑制永磁同步电动机的电磁振动,文中首先建立了转子永磁体磁动势、定子绕组电流磁动势与定子齿槽相互作用产生的径向电磁力的解析分析模型。然后建立了电机的变参数矢量控制系统的场路耦合联合分析模型,以一台11 kW内置式永磁同步电动机为样机,利用机械阻抗法得到了电机主要低阶电磁力产生的电磁振动噪声频谱,确定了对电机电磁振动起主要作用的低阶电磁力的频率。最后利用遗传-蚁群算法,研究了通过优化电机的定子齿槽参数有效削弱具有上述频率的低阶电磁力,从而有效抑制电机的电磁振动。结果显示,利用文中方法确定的定子齿槽参数能有效抑制电机的电磁振动,并且对电机的运行性能产生的影响较小。     

羌塘盆地塞仁地区古油藏地球化学特征及意义

【研究目的】羌塘盆地是青藏高原北部的大型海相含油气盆地,研究区塞仁地区位于南羌塘坳陷,该区油气地球化学研究成果较少、研究程度较低。【研究方法】本文对古油藏含油层样品的族组成、及甾萜烷等地球化学特征进行总结,并结合多种生标参数得出结论。【研究结果】该地区古油藏整体处于低成熟-成熟阶段,C27甾烷较C29甾烷占优势,并且三环萜烷类化合物以C23三环萜烷为主峰,也表明母质来源以海相有机质为主,并有一定的陆源有机质贡献。油藏样品具有较低的姥植比(Pr/Ph<1),非藿烷中检测出一定丰度的伽马蜡烷以及较高的C35/C34升藿烷值特征,这些参数指示古油藏形成于沉积水体较深、还原性相对较强并具有一定盐度的沉积环境。【结论】该地区古油藏地球化学特征分析为油气成藏研究与油气富集规律认识奠定基础,确定了该地区古油藏的沉积环境和母质来源。古油藏母质来源以海相为主,沉积环境为较还原环境。     

高地应力水平岩层隧道滞后型岩爆时空倾向性机制分析

浙江杭温水平岩层隧道内滞后型岩爆频发,但目前对于其孕育机理和时空倾向性研究不足。故采用有限差分软件,通过地应力测试和统计现场岩爆资料的方法,研究分析滞后型岩爆时空特征机制。结果表明:(1)滞后型岩爆具有明显的时空倾向性特征。近70%的滞后型岩爆时间上发生在该区开挖6～30 d,空间上滞后于掌子面30～100 m之间;且多发生中等岩爆,岩爆等级及可能性随时空变化呈现倒“V”形趋势。(2)硬岩在高地应力环境中具有明显的延性与时效变形特征;在卸荷条件下,应力释放率的逐渐增加是诱发滞后型岩爆的最主要因素。(3)开挖一定距离后,隧道周边不同位置处都出现应变能突变,且保持较高的应变能密度,易发生等级较高的岩爆。上述结果为以后预测滞后型岩爆和施加相应支护措施提供了依据。     

Exploration of TCM Masters Knowledge Mining

Traditional Chinese medicine （TCM） has a rich knowledge about human health and disease by its special way evolved along a very long history. As modern medicine is achieving much progress, arguments and disputes toward TCM never end. To avoid losing precious knowledge of living TCM masters, endeavors have been engaged to systematic collection of those knowledge of TCM masters, such as their growth experiences, effective practical cases toward diseases and typical therapeutic principles and methods. Knowledge mining methods have been expected to explore some useful or hidden patterns to unveil some mysteries of the TCM system. In the paper, some computerized methods are applied toward those collected materials about some living TCM masters in China mainland to show a different way of exposing essential ideas of those TCM masters by correspondence visualization which aims to help people understand TCM holistic views toward disease and body, and facilitate tacit knowledge transfer and sense-making of the essence of TCM. The work is one kind of qualitative meta-synthesis of TCM masters＇ knowledge.     

Research on the self-defence electronic jamming decision-making based on the discrete dynamic Bayesian network

The manner and conditions of running the decision-making system with self-defense electronic jamming are given.After proposing the scenario of applying discrete dynamic Bayesian network to the decision making with self-defense electronic jamming,a decision-making model with self-defense electronic jamming based on the discrete dynamic Bayesian network is established.Then jamming decision inferences by the aid of the algorithm of discrete dynamic Bayesian network are carried on.The simulating result shows that this method is able to synthesize different targets which are not predominant.In this way,various features at the same time,as well as the same feature appearing at different time complement mutually;in addition,the accuracy and reliability of electronic jamming decision making are enhanced significantly.     

Krylov subspace method based on data preprocessing technology

The performance of adaptive beamforming techniques is limited by the nonhomogeneous clutter scenario. An augmented Krylov subspace method is proposed, which utilizes only a single snapshot of the data for adaptive processing. The novel algorithm puts together a data preprocessor and adaptive Krylov subspace algorithm, where the data preprocessor suppresses discrete interference and the adaptive Krylov subspace algorithm suppresses homogeneous clutter. The novel method uses a single snapshot of the data received by the array antenna to generate a cancellation matrix that does not contain the signal of interest （SOI） component, thus, it mitigates the problem of highly nonstationary clutter environment and it helps to operate in real-time. The benefit of not requiring the training data comes at the cost of a reduced degree of freedom （DOF） of the system. Simulation illustrates the effectiveness in clutter suppression and adaptive beamforming. The numeric results show good agreement with the proposed theorem.     

New model for load-sharing k-out-of-n: G system with different components

On the basis of capacity flow model, a new model is developed for a load-sharing k-out-of-n： G system consisting of different components, to describe the increase of the same component＇s failure rates under different loads. All components have exponential life distributions and are nonrepairable in the system. Reliability of load- sharing 2-out- of-3： G system is calculated and some special cases for the system are discussed. The calculation and discussions show that the model is right and practical.