高速铁路车站电力谐波分析及抑制

介绍谐波的产生机理及主要分析方法,针对高速铁路车站存在的谐波污染问题,建立车站电力负荷谐波模型进行仿真分析,结合实际测量,得出铁路车站的谐波含量及特征。对铁路车站谐波进行超标率分析表明,按需滤除特征次数谐波设计的无源滤波器一般能够满足国标要求。含无源滤波功能的并联电容器组投切试验表明,合适的分组投切方式下,电容器组能够起到较好的谐波抑制效果。     

铁路牵引供电系统设计中的谐波谐振分析及抑制方案研究

为了避免交直交型电力机车(含动车组)与牵引供电系统之间形成谐波谐振,影响电气化铁路运行安全,有必要在牵引供电系统设计阶段开展谐波谐振特性分析。基于四象限变流器拓扑结构与控制策略,构建电力机车谐波源特性模型,针对某新建电气化铁路牵引供电系统设计方案,构建牵引供电系统数学模型,利用MATLAB/Simulink仿真平台,研究系统谐波谐振特性与变化规律,给出便于工程应用的滤波器设计方案,并验证该方案的可行性。     

中水脱氮实验研究

目前中水厂处理采用的基本工艺对去除污水中氮的效果不好,易造成水体富营养化。由于中水厂出水中氮的含量相对较低,属于微污染水,不适合采用化学方法进行去除,要去除这种水质中的氮考虑采用生物法脱氮。本项目先研究了在慢滤状态,陶粒生物慢滤池对氮的去除效果,继而改进实验装置在慢滤池后加入碎石曝气段及石英砂快滤段,有效地提高了氮的去除效果,氮的去除率基本上都在14％以上,最好时对氨氮去除率可达到28．57％以上。     

涡凹气浮联合固定化曝气生物滤池在含油废水中的应用

采用CAF联合BAF工艺处理高浓度炼油生产废水,并利用浮动环流收油器,对预处理废水中的油类污染物进行回收,无需外加压力,处理成本低。经该工艺二级气浮处理后,油类污染物回收率达到97％。工艺调试运行稳定后,对污染物COD、氨氮、硫化物和石油类进行监测。监测结果表明,COD、氨氮、硫化物和石油类污染物的去除率分别为：96．1％、94．3％、77％和96．7％,出水水质满足GB8978--1996《污水综合排放标准》中第二类污染物最高允许排放浓度一级标准要求。     

液压挖掘机液压系统清洁度的控制

液压系统是液压挖掘机的一个重要组成部分,保持液压系统的清洁度可以降低机器发生故障而停机的几率.主要介绍了通过控制污染物的生成,减少残留污染物和正确选用与合理使用滤油器等方法来控制液压系统的清洁度.     

Wave data assimilation with the Kalman filter

A new data assimilation method for ocean waves is presented, based on an efficient low-rank approximation to the Kalman filter. Both the extended Kalman filter and a truncated second-order filter are implemented. In order to explicitly estimate past wind corrections based on current wave measurements, the filter is extended to a fixed-lag Kalman smoother for the wind fields. The filter is tested in a number of synthetic experiments with simple geometries. Propagation experiments with errors in the boundary condition showed that the KF was able to accurately propagate forecast errors, resulting in spatially varying error correlations, which would be impossible to model with time-independent assimilation methods like OI. An explicit comparison with an OI assimilation scheme showed that the KF also is superior in estimating the sea state at some distance from the observations. In experiments with errors in the driving wind, the modeled error estimates were also in agreement with the actual forecast errors. The bias in the state estimate, which is introduced through the nonlinear dependence of the waves on the driving wind field, was largely removed by the second-order filter, even without actually assimilating data. Assimilation of wave observations resulted in an improved wave analysis and in correction of past wind fields. The accuracy of this wind correction depends strongly on the actual place and time of wave generation, which is correctly modeled by the error estimate supplied by the Kalman filter. In summary, the KF approach is shown to be a reliable assimilation scheme in these simple experiments, and has the advantage over other assimilation methods that it supplies explicit dynamical error estimates.     

Assimilation of altimetric data in the mid-latitude oceans using the Singular Evolutive Extended Kalman filter with an eddy-resolving, primitive equation model

A new data assimilation scheme has been elaborated for ocean circulation models based on the concept of an evolutive, reduced-order Kalman filter. The dimension of the assimilation problem is reduced by expressing the initial error covariance matrix as a truncated series of orthogonal perturbations. This error sub-space evolves during the assimilation so as to capture the growing modes of the estimation error. The algorithm has been formulated in quite a general fashion to make it tractable with a large variety of ocean models and measurement types. In the present paper, we have examined three possible strategies to compute the evolution of the error subspace in the so-called Singular Evolutive Extended Kalman (SEEK) filter: the steady filter considers a time-independent error sub-space, the apprentice filter progressively enriches the error sub-space with the information learned from the innovation vector after each analysis step, and the dynamical filter updates the error sub-space according to the model dynamics. The SEEK filter has been implemented to assimilate synthetic observations of the surface topography in a non-linear, primitive equation model that uses density as vertical coordinate. A simplified box configuration has been adopted to simulate a Gulf Stream-like current and its associated eddies and gyres with a resolution of 20 km in the horizontal, and 4 levels in the vertical. The concept of twin experiments is used to demonstrate that the conventional SEEK filter must be complemented by a learning mechanism in order to model the misrepresented tail of the error covariance matrix. An approach based on the vertical physics of the isopycnal model, is shown particularly robust to control the velocity field in deep layers with surface observations only. The cost of the method makes it a suitable candidate for large-size assimilation problems and operational applications.     

基于小波分析的齿轮箱故障诊断

通过对齿轮箱噪声机理进行研究,建立了相应的数学模型,提出了一种基于小波变换的故障诊断方法.其基本思想是:首先利用小波变换的多分辨率特性,滤除信号的随机噪声,并将提纯后的信号分解到不同的频区;通过对各频区信号进行比较与分析,选取能量集中、包含了调制成分的部分进行复小波变换,利用多尺度小波包络谱获得信号的包络信息;最后,结合傅里叶频谱,确定齿轮箱的故障原因.研究结果表明:该方法能有效识别出齿轮箱系统中轴和齿轮的缺陷,并能锁定故障发生位置、衡量故障程度.     

Using the lead vehicle as preview sensor in convoy vehicle active suspension control

Both ride quality and roadholding of actively suspended vehicles can be improved by sensing the road ahead of the vehicle and using this information in a preview controller. Previous applications have used look-ahead sensors mounted on the front bumper to measure terrain beneath. Such sensors are vulnerable, potentially confused by water, snow, or other soft obstacles and offer a fixed preview time. For convoy vehicle applications, this paper proposes using the overall response of the preceding vehicle(s) to generate preview controller information for follower vehicles. A robust observer is used to estimate the states of a quarter-car vehicle model, from which road profile is estimated and passed on to the follower vehicle(s) to generate a preview function. The preview-active suspension, implemented in discrete time using a shift register approach to improve simulation time, reduces sprung mass acceleration and dynamic tyre deflection peaks by more than 50% and 40%, respectively. Terrain can change from one vehicle to the next if a loose obstacle is dislodged, or if the vehicle paths are sufficiently different so that one vehicle misses a discrete road event. The resulting spurious preview information can give suspension performance worse than that of a passive or conventional active system. In this paper, each vehicle can effectively estimate the road profile based on its own state trajectory. By comparing its own road estimate with the preview information, preview errors can be detected and suspension control quickly switched from preview to conventional active control to preserve performance improvements compared to passive suspensions.     

高速磁悬浮列车间隙信号数字滤波器设计与实现

分析了高速磁浮列车间隙信号噪声的特点,采用基于FPGA的FIR数字滤波器滤除噪声。应用基于位级联的多查找表分布式算法实现16阶低通FIR滤波器,由verilog-HDL语言完成设计文件,并在Simulink及ModelSim ISE 6.1平台上进行了试验仿真,结果均满足设计要求。