基于Hurst指数的油罐声发射信号分析

由油罐声发射检测直接得出油罐底板状态等级的评价研究工作有待完善。提出一种基于Hurst指数理论分析声发射信号幅值最大值分布的评价方法。从Hurst指数分形理论出发,结合声发射信号参数处理方法,给出研究条件假设,分析现场油罐声发射信号结果,并与开罐检测的底板状况加以对比分析。研究发现,相同检测条件,同种类型油罐底板状态等级与Hurst指数呈相反的关系。     

基于空间网格的制导方法研究

针对传统摄动制导修正大干扰能力的缺点,提出一种基于空间网格的制导方法.分析了空间网格法的基本原理,对其建立的要素和具体方法进行了详细说明.并从3个不同侧面对该方法的规律性进行了分析.通过仿真,证明空间网格法有效可行,具有弹上计算简单,数据存储量少,控制易实现,能实时修正大干扰偏差的优点.使其在提高导弹的制导精度和弹上计算效率方面,具有一定的应用前景和参考价值.     

习得论对新疆汉语教学的意义

第二语言习得理论对新疆汉语教学有着重要启示。从输入假设和情感过滤假设出发具体讲述了克拉申理论对于新疆汉语有效教学的意义。通过对一线课堂的了解,进一步从理想的输入、要有足够的输入量、学生学习的动力、情感状态对于学生学习双语的重要性等方面反映出习得理论对于双语教学的意义。     

用业务量损失法评估通信网链路的重要性

本文从业务量损失方面来考虑通信网链路的重要性,提出了一种用于评估通信网链路重要性的方法一业务量损失法。该方法根据不同链路故障造成业务量损失率的不同,据此判断链路的重要性。在不同的路由选择方式下,业务量损失法的评估结果也不同。本文考虑了两种路由选择方式,并举例说明了业务量损失法的运用。     

反解法在再入机动弹道设计中的应用研究

简要分析了一般的再入机动弹道设计方法,即正解法.针对正解法对模型依赖性强和对初值非常敏感的问题,提出了一种基于误差补偿的机动弹道设计方法——反解法.该方法从弹道终端出发反解弹道,将计算结果误差转化为机动点参数误差,再通过关机点或中制导的调整进行误差补偿,从而有利于命中精度和打击效果的实现.仿真结果表明,该方法计算简便,对工程应用有一定的参考价值.     

Effects of total pressures and equivalence ratios on kerosene/air rotating detonation engines using a paralleling CE/SE method

In this paper, the kerosene/air rotating detonation engines(RDE) are numerically investigated, and the emphasis is laid on the effects of total pressures and equivalence ratios on the operation characteristics of RDE including the initiation, instabilities, and propulsive performance. A hybrid MPI + OpenMP parallel computing model is applied and it is proved to be able to obtain a more effective parallel performance on high performance computing(HPC) systems. A series of cases with the total pressure of 1 MPa, 1.5 MPa, 2 MPa, and the equivalence ratio of 0.9, 1, 1.4 are simulated. On one hand, the total pressure shows a significant impact on the instabilities of rotating detonation waves. The instability phenomenon is observed in cases with low total pressure (1 MPa) and weakened with the increase of the total pressure. The total pressure has a small impact on the detonation wave velocity and the specific impulse. On the other hand, the equivalence ratio shows a negligible influence on the instabilities, while it affects the ignition process and accounts for the detonation velocity deficit. It is more difficult to initiate rotating detonation waves directly in the lean fuel operation condition. Little difference was observed in the thrust with different equivalence ratios of 0.9, 1, and 1.4. The highest specific impulse was obtained in the lean fuel cases, which is around 2700 s. The findings could provide insights into the understanding of the operation characteristics of kerosene/air RDE.     

Multi-scale traffic vehicle detection based on faster R-CNN with NAS optimization and feature enrichment

It well known that vehicle detection is an important component of the field of object detection. However, the environment of vehicle detection is particularly sophisticated in practical processes. It is compara-tively difficult to detect vehicles of various scales in traffic scene images, because the vehicles partially obscured by green belts, roadblocks or other vehicles, as well as influence of some low illumination weather. In this paper, we present a model based on Faster R-CNN with NAS optimization and feature enrichment to realize the effective detection of multi-scale vehicle targets in traffic scenes. First, we proposed a Retinex-based image adaptive correction algorithm (RIAC) to enhance the traffic images in the dataset to reduce the influence of shadow and illumination, and improve the image quality. Second, in order to improve the feature expression of the backbone network, we conducted Neural Architecture Search (NAS) on the backbone network used for feature extraction of Faster R-CNN to generate the optimal cross-layer connection to extract multi-layer features more effectively. Third, we used the object Feature Enrichment that combines the multi-layer feature information and the context information of the last layer after cross-layer connection to enrich the information of vehicle targets, and improve the robustness of the model for challenging targets such as small scale and severe occlusion. In the imple-mentation of the model, K-means clustering algorithm was used to select the suitable anchor size for our dataset to improve the convergence speed of the model. Our model has been trained and tested on the UN-DETRAC dataset, and the obtained results indicate that our method has art-of-state detection performance.     

A method to determine the shell layout scheme for equipment battlefield damage tests under artillery fire

In this paper,a new method for determining the shell layout scheme is proposed,which can make the equipment damage data by the battlefield damage test resemble as close as possible the actual combat data.This method is based on the analysis of the impact point distribution and effective damage area of equipment.In order to obtain the position of the impact points,an impact point distribution model under artillery fire was established.Similarly,in order to obtain the effective damage area of equipment,the concepts of generalized damage area and task-based equipment functional damage probability were demonstrated,and the corresponding calculation model was established.Through case analysis,the shell layout scheme was effectively obtained,verifying the correctness of the proposed method.     

一种基于兼容度的组合评估方法

分析了单一评估方法的局限性,基于兼容度准则提出一种将综合指数法和功效评分法等常用评估方法组合而成的一种综合评估方法,采用该方法对潜艇声纳的作战性能进行了评估分析.算例分析表明,该方法对于提高评估结果的可信性具有明显的作用.     

未确知性信息的证据理论合成及其应用

针对在装备管理中所采用的专家评估法存在着未确知性现象,提出了一种基于D-S证据合成理论来融合未确知性信息的方法.从而,将每名专家的意见综合为专家组的一致意见,使评估结果更合理.最后,通过实例说明该方法的有效性.