横倾船舶三维非定常扰动势流特性

当船舶出现破损淹舱或者在波浪中做横摇运动时,船体都会出现横倾,这会使得船舶在水面下的湿表面与正浮时不再相同,船体周围的非定常流场因此会发生改变。本文基于三维线性势流理论,使用奇点分布法对具有不同横倾角的Wigley III船型的非定常扰动速度势展开计算,进而求解Wigley III船型水动力系数与波浪激励力。计算结果表明,横倾对垂荡、横摇、纵摇水动力系数的影响比较明显;在顶浪下,横倾对横向的波浪激励力影响显著。     

海战场作战资源标识框架研究

由于海战场的特殊性,以及海战场作战对资源规划和管理的要求,海战场作战资源标识成为海战场作战的关键技术之一。本文在明确海战场作战资源概念的基础上,对XML、RDF、本体、语义网等4种资源标识技术进行分析,选取语义网技术作为资源标识技术。然后设计海战场作战资源标识框架和框架实现流程,详细介绍资源标识结构和过程。最后对本文的研究工作进行总结,展望作战资源标识的发展趋势。     

实时信号检测在水下信号识别中的研究及系统仿真

舰船作为一种军民两用的交通工具,既是一种重要的交通运输工具,又是一种重要的军事装备。不论是在民用领域,还是在军用领域,都需要对水下信号进行检测和识别。由于电磁波在水中传播的干扰较大且衰减较快,电磁波在水下通信领域的应用较少。现在普遍采用声波作为水下通信的主要方式,本文对水声通信系统及对相关检测技术进行仿真分析,验证相关检测技术在水下信号识别中的应用价值。     

LKD1-T型列控中心的工程接口和现场调试方法

LKD1-T型列控中心是全路使用最广的既有线列控中心设备。本文介绍了LKD1-T型的工程接口，针对列控中心开通的准备工作和现场调试方法进行了详细阐述，对于帮助和指导现场人员和施工单位、电务工作人员熟悉列控中心设备原理，进行现场开通调试，具有一定指导意义。     

大数据驱动的新能源汽车多维度安全预警建模方法研究

新能源汽车安全已是一个非常严峻的现实问题,直接影响到产业的未来与发展。综合阐述了基于大数据驱动的安全预警技术建模的方法学问题。从多个层次、多个维度讨论了安全预警的技术方法,重点分析提出了基于系统稳定性、相关性、一致性等累计风险模型与事故特征匹配追踪两大类模型。介绍稳态概率计算方法、累计风险计算方法、风险曲线识别方法。介绍了基于中心距、能量一致性的累计风险模型与应用情况,最后介绍一类全新的模式匹配识别模型:事故特征匹配追踪模型。总结提出了从微观定义安全、宏观预警安全、智能完善安全、数据保障安全一个比较完整的安全预警体系与方法。     

测试技术在齿轮工艺质量分析中的应用

首先以微观与宏观相结合的方法,分析了齿轮加工中的误差源.其次,以模糊逻辑误差诊断方法为基础,对齿轮加工误差源诊断问题进行了分析研究,并结合实际工作,介绍了诊断实例.     

电气化铁道对电能质量影响的割集分析法

从分析电气化铁道对电网电能质量影响的需求出发,采用割集原理为局部电网建立了适合进行电能质量评估的模型,并利用模拟短路的方法得到了外部电网的广义多端口诺顿等值电路参数。在此基础上考虑多个干扰源共同作用下,评估了胶济电气化铁道负序与谐波对山东电网电能质量的影响。     

基于太阳辐射效应校正的高原铁路廊道地热异常区识别研究

为提高热红外遥感识别地热异常区的准确度，选取高原铁路廊道作为研究区，基于Landsat8数据采用单窗算法反演得到白天地表温度，并基于ECO2LSTE数据得到夜间地表温度；然后，利用随机森林方法选取海拔、坡度、坡向、累积太阳辐射、NDVI、NDSI、NDWI以及反照率作为输入因子，得到去除太阳辐射效应的地表温度；最后，选取去除太阳辐射效应的地表温度、断裂密度、到水系距离和地磁异常作为指标因子，采用确定性系数模型定量识别地热异常区，并利用已知温泉点对结果进行评价。结果表明： 1）随机森林方法可有效去除非地热引起的温度变化，减弱太阳辐射效应，提高地热异常区识别的准确度； 2）地热异常区评价结果与已知温泉点分布较为一致，高异常区和中异常区的识别结果可靠； 3）高原铁路廊道主要途经7个地热异常区，经过高异常区和中异常区的廊道长度分别为72 km和125 km，泸定—康定、理塘盆地及周边、巴塘、贡觉、昌都—察雅、八宿、波密—鲁朗是需要重点防范高温热害的区段。研究结果初步实现了高原铁路廊道的地热异常区定量化和精细化识别。     

Experimental modeling of controlled suspension vehicles from onboard sensors

In this article, identification of vertical dynamics of vehicles with controlled suspensions is considered. Identification is performed from experimental data measured on a four-poster bench test of a segment C car, equipped with a CDC-Skyhook dampers control system. The measurements are obtained from the onboard accelerometers needed by the control system. A nonlinear model in regression form is identified, having the road profile and damper control currents as inputs and chassis accelerations as outputs. The model is identified by means of a set membership structured identification method, which takes advantage of physical information on the structure of the system, decomposing the system into three subsystems: one represents the chassis and engine and the other two represent the overall behavior of front and rear suspensions, wheels and tires. This decomposition allows us to avoid the complexity accuracy problems derived from the high dimension of required regression space. Indeed, the overall high-dimensional identification problem is reduced to the identification of lower dimensional subsystems and to the estimation of their interactions. An iterative scheme is used for solving the decomposed identification problem. As the chassis pitch is small for the usual road profiles, the chassis-engine block is considered linear and standard linear methods are used for its identification. The other two subsystems are the main sources of nonlinearities in the system, mainly due to the significant nonlinearities of controlled dampers and of tires. Owing to the complexity/accuracy problems of a physical modeling of these subsystems, an input–output approach is taken. In particular, a nonlinear set membership method that does not require the search of the functional form of involved nonlinearities is used for the identification of these subsystems. The iterative algorithm converged in two iterations to a model providing a quite satisfactory simulation accuracy for all the considered road profiles and CDC-Skyhook settings.     

The effect of the inflation pressure of tyres on motorcycle weave stability: experiments and simulation

Increasing the stability of a motorcycle requires an understanding of the optimal conditions of the tyre. The inflation pressure is one of the main parameters that directly affects the tyre properties, which in turn influences motorcycle stability and safety. This paper focuses on the effect of the inflation pressure of the tested tyres on motorcycle weave stability. Experimental data are collected from tests carried out in straight running at constant speed. The data analysis is based on stochastic subspace identification methods. Simulations are performed using an advanced motorcycle multi-body code with parameters measured from the tested vehicle. Finally, the comparison between simulations and experimental tests is discussed. The research results show an agreement between experimental tests and simulations where weave stability increases with inflation pressure for the specified range of tyre pressure.