Correcting Acoustic Doppler Current Profiler Discharge Measurements Biased by Sediment Transport

A negative bias in discharge measurements made with an acoustic Doppler current profiler (ADCP) is attributed to the movement of sediment on or near the streambed, and is an issue widely acknowledged by the scientific community. The integration of a differentially corrected global positioning system (DGPS) to track the movement of the ADCP can be used to avoid the systematic bias associated with a moving bed. DGPS, however, cannot provide consistently accurate positions because of multipath errors and satellite signal reception problems on waterways with dense tree canopy along the banks, in deep valleys or canyons, and near bridges. An alternative method of correcting for the moving-bed bias, based on the closure error resulting from a two-way crossing of the river, is presented. The uncertainty in the mean moving-bed velocity measured by the loop method is shown to be approximately 0.6?cm/s. For the 13 field measurements presented, the loop method resulted in corrected discharges that were within 5% of discharges measured utilizing DGPS to compensate for moving-bed conditions.     

Improving Precision in the Reference Velocity of ADCP Measurements Using a Kalman Filter with GPS and Bottom Track

Global positioning system (GPS) data are used to measure boat velocity during acoustic Doppler current profiler (ADCP) discharge measurements, particularly when bottom tracking (BT) is biased by moving bed. A Kalman filter is developed to improve the velocity reference used by the ADCP under such conditions. Kalman filtering is a recursive statistical technique that estimates the current state of a process, given various inputs and their variance. In the case of data obtained by ADCP, the availability of two independent velocity measurements and a position measurement makes this method particularly attractive. The new Kalman filter combines raw inputs for GPS position (GGA) and Doppler velocity (VTG) with BT data in real time to produce best estimates of velocity. The technique is evaluated and calibrated using various accuracies of GPS data collected simultaneously along with unbiased BT data at two different sites. On the Gatineau River, real-time kinematic and wide area augmentation system corrections were used for this study. On the Saint Mary’s River, nondifferential GPS was collected. To examine the conditions under which such a system would be required, synthetic data for a moving bed contamination of BT were created. In all moving bed conditions evaluated, the Kalman filter estimates of reference velocity were superior to raw inputs.     

Aircraft Icing Detection, Identification, and Reconfigurable Control Based on Kalman Filtering and Neural Networks

Flight in all weather conditions has necessitated correctly detecting icing and taking reasonable measures against it. This work aims at the detection and identification of airframe icing based on statistical properties of aircraft dynamics and reconfigurable control protecting aircraft from hazardous icing conditions. A Kalman filter is used for the data collection for the detection of icing, which aerodynamically deteriorates flight performance. A neural network process is applied for the identification of icing model of the aircraft, which is represented by five parameters based on past experiments for iced wing airfoils. Icing is detected by a Kalman filtering innovation sequence approach. A neural network structure is embodied such that its inputs are the aircraft estimated measurements and its outputs are the parameters affected by ice, which corresponds to the aircraft inverse dynamic model. The necessary training and validation set for the neural network model of the iced aircraft are obtained from the simulations of nominal model, which are performed for various icing conditions. In order to decrease noise effects on the states and to increase training performance of the neural network, the estimated states by the Kalman filter are used. A suitable neural network model of aircraft inverse dynamics is obtained by using system identification methods and learning algorithms. This trained model is used as an application for the control of the aircraft that has lost its controllability due to icing. The method is applied to F16 military and A340 commercial aircraft models and the results seem to be good enough.     

平方根卡尔曼滤波分光光度法同时测定钼、钨和锡

本文提出了平方根卡尔曼滤波分光光度法同时测定钢样中钼、钨、锡含量的新方法。平方根卡尔曼滤波是对普通卡尔曼滤波的改进，以克服由计算中截尾误差引起的滤波数值发散。它能有效地滤除信号中的高斯白噪声和分辨重叠峰。实验时采用苯基荧光酮－ＣＴＭＡＢ三元络合物显色体系，对合成样品及实际钢样的分析结果满意。由于不需分离，方法简便快速。     

Effects of Sediment Concentration and Initial Phosphorus Loading on Phosphate Adsorption in the Chongqing Reach of the Yangtze River

The results are presented from a laboratory and theoretical study to investigate the effects of sediment concentration and initial phosphorus loading on adsorption isotherm and capacity. The tested aquatic sediment was collected from the Chongqing reach of the Yangtze River. The adsorption isotherm of dissolved phosphate was approximated by the Langmuir equation. Using mass conservation and Langmuir adsorption kinetic equations, the authors derived formulas for calculating both the particulate and dissolved phosphate concentration. Kinetic experiments on fine sediment samples (<0.008?mm) show that the adsorption process is time dependent and takes place in three stages, namely, an initial fast stage followed by a gradual adsorption, leading to the eventual equilibrium. The results indicate that larger initial phosphate loading causes longer duration, higher adsorption rate, and less adsorption percentages on both the first and second stages. The sediment concentration mainly influences the adsorption rate of the first stage, in which the adsorption rate significantly increases with the increasing sediment concentration.     

乙酸纤维素富集原子吸收光谱法测定金

研究了用乙酸纤维素分离富集原子吸收光谱法测定矿石中的金时各种影响因素，试验了若干种阴、阳离子存在下的干扰情况。该法操作简便、富集倍数高，其精密度和准确度都令人满意。     

基于卡尔曼滤波和高频信号注入法的永磁同步电机转子位置自检测

永磁同步电机的运动控制是一个强耦合的非线性动态控制系统,而且在控制过程中测量数据带有噪声,采用传统的线性控制理论很难达到系统要求.提出一种非线性系统的随机观测器——卡尔曼位置观测器,它用于高频信号注入法下的转子位置检测.利用脉动高频信号注入法进行永磁同步电机转子位置自检测,将产生的高频载波电流解调后,送入设计的卡尔曼位置观测器,可有效去除干扰噪声,准确观测出转子位置.仿真实验结果表明,在有系统噪声和测量噪声的情况下,基于卡尔曼位置观测器的脉动高频信号注入法能够精确地跟踪转子位置.     

Control of Turbidity Currents in Reservoirs by Solid and Permeable Obstacles

Turbidity currents are often the main process for the transport and deposition of the sediments in narrow, alpine reservoirs. These underwater avalanches with high concentration of suspended sediments follow the thalweg of the lake to the deepest area near the dam, where the sediments can affect the operation of the bottom outlet and the intake structures. To control the sedimentation within the reservoir, the effects of solid and permeable obstacles on the turbidity current were investigated with physical experiments and numerical simulations. In the physical experiments, the velocity distributions as well as the spatial and temporal evolution of the deposits were measured. The investigated measures were also simulated by means of a two-dimensional numerical model, based on the flow solver CFX-4.4. The investigations showed that turbidity currents can be influenced effectively by properly designed constructive measures. Based on the results of the physical experiments and numerical simulations, some design recommendations for solid and permeable obstacles are proposed.     

h.264帧内预测算法及其在解码器中的硬件实现

介绍了h.264标准的帧内算法,提出了一种并行结构,可以处理包括16×16,4×4块,以及最新标准中8×8块共26种帧内预测模式。在分析各种预测模式的运算相似性的基础上,提出了一种可重用结构,并使用veril-ogHDL硬件描述语言进行了实现。仿真结果表明,该设计适用于在4∶2∶0制式下,720×480,30帧/s的视频的实时解码。