弹载高g值三轴加速度测试系统技术分析

为准确分析弹丸在内弹道运动时的加速度特点,本文设计了一种基于动态存储测试技术的弹载高g值三轴加速度测试系统.文章介绍了系统组成及关键技术,这些关键技术为系统在恶劣的测试环境中能准确测得实验数据提供了保障.最后,对实测得的轴向和径向加速度数据分别进行了处理及分析并得出了相关结论.该测试系统具有实际工程使用价值,可为分析膛炸现象提供一种有效的测试手段.     

压电振动能量采集器的力电耦合模型及其功率优化*

为提高传统压电振动能量采集器集总参数模型的性能预测精度,考虑悬臂梁的振型信息与轴向应变分布情况,提出了一种改进的力电耦合模型,该模型引入无因次幅值修正因子,通过曲线拟合方法确定了修正因子与振型函数和振动幅值之间的关系表达式;利用Rayleigh-Ritz模态分析法确定了力电耦合模型中的集总等效参数(如质量、刚度等),并根据弹性动力学原理建立了能量采集器的运动控制方程,得到了稳态时能量采集器的力、电输出响应表达式;最后,利用改进的模型对能量采集器的负载电阻和输出功率进行了优化,得到了负载短路和负载开路时能量采集器的最优输出特性。仿真结果与实例对比验证了提出模型的正确性,表明改进的力电耦合模型具有较高的预测精度。     

自供电磁阻车辆检测节点设计

针对无线车辆信息采集系统寿命受制于节点功耗的问题,设计了一种基于各向异性磁阻传感器的自供电车辆检测节点。节点采用电源动态管理,设计了快速信号采集电路,结合低功耗芯片的选用以及执行睡眠等方法来控制节点功耗。为减少通信次数和保证可靠通信,针对应用定制了时分多址加跳频的无线通信协议。节点采用超级电容加充电锂电池的存储结构收集太阳能,通过软硬件协同设计实现了简单高效的能量管理方法,具有供电源自动切换和充电控制功能。实验测试的结果表明该节点能够胜任车流量检测应用,自供电能够满足节点可持续工作的需要。     

地铁车轮振动声辐射特性和车轮降噪

为降低地铁车轮振动噪声,建立车轮三维有限元模型实体网格,利用有限元法计算车轮的固有频率和模态振型;将径向单位力激励下的车轮表面振动速度作为边界条件,采用直接边界元法分析车轮振动声辐射特性;利用阻尼措施降低车轮辐射噪声.结果表明：轮辐和踏面是产生高频噪声的主要部位,在3 731.3 Hz的声功率级最高为69.2 dB(A),此频率下轮辐对总声压贡献最大;采用阻尼措施后声功率级最高值下降4.7 dB(A).数值仿真结果可以为低噪声车轮的研究提供参考.     

一种高效的H.264反变换反量化结构设计

在分析H.264反变换反量化算法的基础上,提出了一种高效的H.264反变换反量化硬件结构.在反变换中,采用了一个可重构的一维IDCT变换结构;在反量化中,采用了4个反量化单元的并行结构,并通过LUT取代了占用电路面积大的模运算和除法运算;在整体结构设计中,采用了门控时钟方案和流水线技术.结果表明,本设计可提高系统输出能力和降低硬件功耗,并满足1080i高清码流实时解码的要求.     

水布垭水电站工程施工供电系统功率因数改善方法研究

水布垭水电站工程施工供电系统的110kV主供电源的输电线路因长线路＂充电功率＂效应的影响,致使该供电系统的功率因数低,线路的有功功率损耗大。通过对该系统的分析和研究,采取终端变电所低功率因数运行的方式,增大终端的感应无功功率,以冲减输电线路的充电无功功率,从而提高了供电系统的功率因数,减少了输电线路的有功损耗,为该工程的建设减了生产成本。     

基于新技术的水力发电厂直流系统

介绍了采用新技术的流溪河发电厂直流系统。该直流系统采用总线控制方式,对所监测的模拟量、数字量无数量限制,其通道数可任意扩展;由于采用智能控制技术,系统具有较强的容错能力,而且响应速度快、噪音小、输出稳定,完全满足发电厂的安全生产要求。     

First-order side channel attacks on Zhang’s countermeasures

Zhang’s three countermeasures are known to be secure against certain first-order side channel attacks such as differential power analysis and correlation power analysis. This security comes from the countermeasures’ use of random points to blind the message and random integers to blind the secret scalar. In this paper, we propose first-order side channel attack methods that can perfectly break these three countermeasures. Even though Zhang’s countermeasures use random points and random integers our attacks are made possible by the fact that intermediate values computed by these countermeasures are dependent on specific values that we can guess. The experimental results verify that the proposed attack methods can successfully break existing countermeasures.     

A Faà di Bruno Hopf algebra for a group of Fliess operators with applications to feedback

A Faà di Bruno type Hopf algebra is developed for a group of integral operators known as Fliess operators, where operator composition is the group product. Such operators are normally written in terms of generating series over a noncommutative alphabet. Using a general series expansion for the antipode, an explicit formula for the generating series of the compositional inverse operator is derived. The result is applied to analytic nonlinear feedback systems to produce an explicit formula for the feedback product, that is, the generating series for the Fliess operator representation of the closed-loop system written in terms of the generating series of the Fliess operator component systems. This formula is employed to provide a proof that local convergence is preserved under feedback.     

Bayesian analysis of robust Poisson geometric process model using heavy-tailed distributions

We propose a robust Poisson geometric process model with heavy-tailed distributions to cope with the problem of outliers as it may lead to an overestimation of mean and variance resulting in inaccurate interpretations of the situations. Two heavy-tailed distributions namely Student’s t and exponential power distributions with different tailednesses and kurtoses are used and they are represented in scale mixture of normal and scale mixture of uniform respectively. The proposed model is capable of describing the trend and meanwhile the mixing parameters in the scale mixture representations can detect the outlying observations. Simulations and real data analysis are performed to investigate the properties of the models.