一种新的``弹簧振子-单摆'耦合摆研究

介绍了一种新发现的``弹簧振子-单摆'耦合摆. 采用拉格朗日方 程推导出了耦合摆的运动微分方程. 进一步根据耦合摆 的实际参数,利用Matlab软件进行了数值计算,发现耦合摆的弹簧振子振幅与单摆的摆幅此 消彼长,系统的能量在两者之间不断交换,呈周期性变化,与实际符合很好. 通过作出耦合 摆的轨迹图,发现与实际一致. 最后,分析了耦合摆实现的条件.     

基于微小型传感器的惯性/卫星/天文组合导航方法

为了实现基于微小型传感器的高精度导航,针对微小型导航传感器精度相对较低、误差相对较大的特点,对微小型惯性测量单元(MIMU)、微GPS卫星接收机、微小型星敏感器的测量误差进行了建模与分析;对多传感器的导航信息进行分散化处理,采用卡尔曼滤波进行局部估计;提出了基于部分信息融合的联邦滤波算法进行全局融合;并给出了利用全局融合结果对MIMU导航误差进行输出校正的算法.仿真结果表明,该组合导航方法能够利用微小型传感器实现较高精度的导航定位.     

基于神经网络的无陀螺捷联惯导系统姿态预测

在无陀螺捷联惯导系统中,以工程问题为研究背景,针对以往解算载体角速度精度不高,导航误差随时间积累较快的问题,提出了基于信息融合理论的BP神经网络模型预测飞行体姿态的系统,并采用LM算法,提高学习速度.在研究了加速度传感器输出信号对飞行体姿态影响的基础上,将加速度计的输出信息作为输入变量,飞行体的实时三轴角速度作为目标信号建立网络模型.选取测试样本进行训练,得到较高精度的角速度输出,再运用四元数法解算姿态角,从一定程度上抑制了误差的积累.仿真结果表明该优化算法收敛速度快,对角速度的预测精度较高,并且合理选择及增加样本信息可以提高网络的泛化能力,为该系统走向工程实践提供了理论依据.     

无陀螺惯性测量单元设计及仿真分析

在简述无陀螺惯性测量单元(GF-IMU)测量角速度的一般原理的基础上,提出了一种九加速度计的配置方案及其角速度解算方法.该算法利用加速度计输出的测量信息直接求得所测量的角速度的绝对值,没有积分运算引入的迭代误差,在一定程度上提高了载体角速度的解算精度.针对该九加速度计配置方案在解算载体角速度时,存在需要开方及符号误判等不足,提出一种解算角速度的微分算法,彻底消除解算过程中开方及符号判断带来的误差,提高了系统精度和实时性.仿真分析证明了方案的可行性和算法的有效性.     

组合滤波器在组合导航中的应用设计

设计了基于INS GPS组合导航系统的组合滤波器(卡尔曼滤波器和H∞滤波器)及实现方法,建立了9维系统状态方程,给出了陀螺误差模型、加计误差模型和GPS误差模型,实现了以GPS与INS输出的东、北向速度误差作为组合滤波器观测量的组合方案.该组合滤波器通过检测各子滤波器的估计误差量的均值,使其自身具有很强的自诊断能力.通过计算机的仿真,对系统的精度进行了分析,证明该方案是可行的,能够加快计算速度,实现实时滤波计算,取得很好估计效果.     

基于Simulink和FlightGear软件的机载惯性测量单元仿真

包含动力学和运动学特性的机载IMU数据对于飞行对准等惯性系统算法研究具有重要意义。基于人在回路仿真的思想,设计了一种可包含完整飞机模型,不需要设计特定的自动驾驶仪,来实现任意机动下机载惯性测量单元仿真的方案。给出了惯性测量单元仿真模型,设计了基于Simulink、AeroSim模块集及FlightGear模拟飞行软件的新方案,实现了一个机载惯性测量单元的仿真模型,该模型采用飞行摇杆,由人实现对飞机的控制和机动飞行。仿真结果表明,采用该仿真方案,避免了复杂的自动驾驶仪设计,可以得到机动飞行条件下的机载惯性测量单元仿真数据和导航参数基准数据,方案切实可行。     

基于虚拟节点连接的道路网络模型

利用传统的基于节点连接的道路网络模型来表达真实世界中的道路网络,其存在的缺陷越来越突出,大大降低了导航系统的鲁棒性。为了消除这些缺陷,提出一个新的道路网络模型,即基于虚拟节点连接的道路网络模型;其虚拟节点是汇交路段的各个端点所围成的区域,具有真实道路路口的形状。与传统模型相比,该模型更能表达真实世界道路网络中的交通流,所以它能更好地满足地图匹配理论要求。另外,该模型能很好地表达真实道路路口参数,所以它在交通规划、交通管理和交通流模拟中都有着十分广阔的应用前景。     

Virtual experimentation through 3D full-loop simulation of a circulating fluidized bed

Eulerian granular multiphase model with a drag coefficient correction based on the energy-minimization multi-scale （EMMS） model was used to simulate a semi-industry scale circulating fluidized bed （CFB）. Three-dimensional （3D）, time-dependent simulation of a full-loop CFB revealed that the axial profiles of cross-sectionally averaged solid volume fraction, and the radial profiles of solid axial velocity and solid volume fraction were in reasonable agreement with experimental data. Based on this agreement, database derived from experiments not yet accomplished was replenished with such simulations, and fluid regime diagrams and pressure balance around the CFB loop were derived accordingly. This work presents an integrated viewpoint on CFB and unfolds a fresh paradigm for CFB modeling, which can be expected to help resolve certain issues long in dispute but bard for experiments.     

Assessing mixing characteristics of particle-mixing and granulation devices

The mixing of particulates such as powders is an important process in many industries including pharmaceuticals, plastics, household products （such as detergents） and food processing. The quality of products depends on the degree of mixing of their constituent materials which in turn depends on both geometric design and operating conditions. Unfortunately, due to lack of understanding of the interaction between mixer geometry and the granular material, limited progress has been made in optimizing mixer design. The discrete element method （DEM） is a computational technique that allows particle systems to be simulated and mixing to be predicted. Simulation is an effective way of acquiring information on the performance of different mixers that is difficult and/or expensive to obtain using traditional experimental approaches. Here we demonstrate how DEM can be used to unravel flow dynamics and assess mixing in several different types of devices. These devices used for mixing and/or granulation of particulates, are classified broadly as gravity controlled, bladed and high shear. We also explore the role of particle shape in mixing performance and use DEM to test whether Froude number scaling is suitable for predicting scale performance of rotating mixers.     

Pattern formation in particle systems driven by color field

The structural evolution of systems with two kinds of particles driven in opposite directions, i.e., driven by a color field, is investigated by molecular dynamics simulations. Gaussian thermostat, a common treatment to restrict the thermal velocity of the particles in the systems, has been used so as to account for the dissipation of heat and allow the system to reach a steady state. It has been found that with the increase of the strength of driving force （F）, the system undergoes an obvious structural transition from an initially random mixing state to a state characterized by separate lanes and in each lane only one kind of particles exists. The analysis shows that the reason for the formation of lane structure is not only the increase of F but also the variation of particle friction coefficient. While using Gaussian thermostat the particle friction coefficient becomes a function of F. Increasing F leads to high particle friction coefficient and inevitably results in lane formation for strong enough driving force. When lifting the effect of F on friction coefficient and choosing a constant friction coefficient, our results show that for a given F there always exists a critical value of friction coefficient higher than which the system will develop into lane structure.