凌庄子水厂保水堰流量系数试验

凌庄子水厂蓄水池进水口处有一保水堰,为非标准薄壁堰,不能使用已有堰流公式对其过流量进行准确计算。为了得出较为精确的过流流量,按照重力相似准则制作几何比尺为1∶5的模型进行试验研究。在已有自由出流公式的基础上,对自由出流流量系数进行修正并对淹没情况下流量变化过程进行研究。对该非标准堰自由出流流量系数的实测值与经验值进行分析比较,发现堰板槽降低了实际自由出流过流能力。淹没出流的流量系数主要与下游尾水位有关,试验中形成的淹没式堰流受实际堰型尺寸影响,下游尾水位和堰上水位近似相等,不完全适用已有淹没出流流量公式,通过试验给出了修正淹没系数随h/p的变化关系。结果表明利用堰前、堰后水位初步计算过流流量是可行的,可为该工程提供参考,也可为实际工程中非标准矩形堰的流量计算提供思路。     

自然循环窄矩形通道内过冷沸腾两相摩擦阻力特性

采用去离子水作为实验工质，在低压低流速自然循环工况下开展了单面加热可视化窄矩形通道内的过冷沸腾摩擦阻力特性实验研究。实验中测量了实验段内的压降数据，并通过高速摄影仪拍摄了窄矩形通道内的气液两相图像，提出了过冷沸腾条件下的两相摩擦压降的剥离计算方法。基于本实验中获得摩擦压降数据，对分别基于均相流模型和分液相模型的经典两相摩擦压降计算关系式进行了评估，实验结果表明：采用不同等效黏度计算方法的均相流模型计算结果比实验值明显偏小；而分相流模型中，Sun and Mishiba关系式和Tran关系式均能够较好地预测摩擦阻力，计算值与实验值的平均相对偏差在±15%以内。结合实验数据，以分相流模型方法为基础，考虑全液相Reynolds数、Martinelli参数和Laplace数的影响，获得了计算分液相折算系数的经验关系式，与实验数据符合较好, 平均相对误差在10%范围内。     

Off‐grid DoA estimation method of wideband signals

In this paper, an off‐grid direction of arrival (DoA) estimation method is proposed for wideband signals. This method is based on the sparse representation (SR) of the array covariance matrix. Similar to the time domain DoA estimation methods, the correlation function of the sources was assumed to be the same and known. A new measurement vector is obtained using the lower‐left triangular elements of the covariance matrix. The DoAs are estimated by quantizing the entire range of continuous angle space into discrete grid points. However, the exact DoAs may be located between two grid points; therefore, this estimation has errors. The accuracy of DoA estimation is improved by the minimization of the difference between the new measurement vector and its estimated values. Simulation results revealed that the proposed method can enhance the DoA estimation accuracy of wideband signals.     

干扰条件下的“北斗”信号解扩重构DOA估计

在干扰条件下，卫星导航抗干扰波束形成算法往往需要卫星信号波达方向（Direction-of-Arrival，DOA）的先验信息。但当存在低信噪比信号或主动干扰源时，常规的DOA估计算法性能急剧下降甚至失效。针对此问题，提出了一种被干扰信号压制的低信噪比“北斗”信号的DOA估计算法。该算法首先通过对接收信号进行子空间投影抑制干扰信号，然后对抑制干扰后的信号进行解扩重构处理，最后通过多重信号分类算法完成对“北斗”信号的DOA估计。仿真结果表明，在干扰信号干信比80 dB条件下，“北斗”信号DOA估计误差在5°以内，为下一步进行波束形成计算提供了高精度的入射角信息。     

Rectangular Section Control Technology for Silicon Steel Rolling

Rectangular section control technology(RSCT)was introduced to achieve high-precision profile control during silicon steel rolling.The RSCT principle and method were designed,and the whole RSCT control strategy was developed.Specifically,RSCT included roll contour design,rolling technology optimization,and control strategy development,aiming at both hot strip mills(HSMs)and cold strip mills(CSMs).Firstly,through the high-performance variable crown(HVC)work roll optimization design in the upper-stream stands and the limited shifting technology for schedule-free rolling in the downstream stands of HSMs,a hot strip with a stable crown and limited wedge,local spot,and single wave was obtained,which was suitable for cold rolling.Secondly,an approximately rectangular section was obtained by edge varying contact(EVC)work roll contour design,edge-drop setting control,and closed loop control in the upper-stream stands of CSMs.Moreover,complex-mode flatness control was realized by coordinating multiple shape-control methods in the downstream stands of CSMs.In addition,the RSCT approach was applied in several silicon-steel production plants,where an outstanding performance and remarkable economic benefits were observed.     

Nonuniform linear array DOA estimation using EM criterion

In this letter, we address the problem of Direction of Arrival (DOA) estimation with nonuniform linear array in the context of sparse Bayesian learning (SBL) framework. The nonuniform array output is deemed as an incomplete-data observation, and a hypothetical uniform linear array output is treated as an unavailable complete-data observation. Then the Expectation-Maximization (EM) criterion is directly utilized to iteratively maximize the expected value of the complete-data log likelihood under the posterior distribution of the latent variable. The novelties of the proposed method lie in its capability of interpolating the actual received data to a virtual uniform linear array, therefore extending the achievable array aperture. Simulation results manifests the superiority of the proposed method over off-the-shelf algorithms, specially on circumstances such as low SNR, insufficient snapshots, and spatially adjacent sources.     

基于三相幅度测量的相控阵天线快速校准方法

提出了一种基于三相幅度测量的相控阵天线快速校准方法。该方法将天线阵列进行分组,利用每种分组在三种配相下的阵面合成场幅度测量值,可解算出各个天线单元的初始幅相值。该方法仅需幅度测量,避免了相位测量误差影响单元幅相值的计算精度,而且所需幅度测量次数仅为(2N+1)次,可显著提高校准时效性。另外,利用分组思想,同时改变多个单元相位,使总辐射场的幅度变化显著,提升校准准确性。仿真结果表明:校准后相位均方根误差为2.2°,幅度均方根误差为0.2 dB。     

Study on maximum power point tracking of photovoltaic array in irregular shadow

Traditional maximum power point tracking (MPPT) methods can hardly find global maximum power point (MPP) because output characteristics curve of photovoltaic (PV) array may have multi local maximum power points in irregular shadow, and thus easily fall into the local maximum power point. To address this drawback, Considering that sliding mode variable structure (SMVS) control strategy have such advantages as simple structure, fast response and strong robustness, and P&O method have the advantages of simple principle and convenient implementation, so a new algorithm combining SMVS control method and P&O method is proposed, besides, PI controller is applied to reduce system chattering caused by switching sliding surface. It is applied to MPPT control of PV array in irregular shadow to solve the problem of multi-peak optimization in partial shadow. In order to verity the rationality of the proposed algorithm, the experimental circuit is built, which achieves MPPT control by means of the proposed algorithm and P&O method. The experimental results show that compared with the traditional P&O algorithm, the proposed algorithm can fast track the global MPP, tracking speed increases by 60% and the relative error decreased by 20%. Moreover, the system becomes more stable near the MPP, the fluctuations of output power is greatly reduced, and thus make full use of solar energy.     

Bond graph modeling,design and experimental validation of a photovoltaic/fuel cell/ electrolyzer/battery hybrid power system

This work presents a complete bond graph modeling of a hybrid photovoltaic-fuel cell-electrolyzer-battery system. These are multi-physics models that will take into account the influence of temperature on the electrochemical parameters. A bond graph modeling of the electrical dynamics of each source will be introduced. The bond graph models were developed to highlight the multi-physics aspect describing the interaction between hydraulic, thermal, electrochemical, thermodynamic, and electrical fields. This will involve using the most generic modeling approach possible for managing the energy flows of the system while taking into account the viability of the system. Another point treated in this work is to propose. In this work, a new strategy for the power flow management of the studied system has been proposed. This strategy aims to improve the overall efficiency of the studied system by optimizing the decisions made when starting and stopping the fuel cell and the electrolyzer. It was verified that the simulation results of the proposed system, when compared to simulation results presented in the literature, that the hydrogen demand is increased by an average of 8%. The developed management algorithm allows reducing the fuel cell degradation by 87% and the electrolyzer degradation by 65%. As for the operating time of the electrolyzer, an increment of 65% was achieved, thus improving the quality of the produced hydrogen. The Fuel Cell's running time has been decreased by 59%. With the ambition to validate the models proposed and the associated commands, the development of this study gave rise to the creation of an experimental platform. Using this high-performance experimental platform, experimental tests were carried out and the results obtained are compared with those obtained by simulation under the same metrological conditions.     

低觉醒脑电识别与唤醒的可穿戴系统研究

为智能化地识别警戒作业人员出现的低觉醒、注意力下降的生理状态，本文介绍了一种基于FPGA和脑电信号处理的低觉醒状态检测与唤醒系统，系统通过传感器从大脑头皮采集脑电信号，转换为数字信号，经傅里叶变换获取了脑电信号的θ相对能量、α相对能量、重心频率、谱熵等4个特征量，由4个特征量表征低觉醒状态并运用支持向量机对低警戒状态进行识别，当识别出低觉醒状态时采用声音报警模块发出声音，唤醒警戒作业人员。设计系统能够较好地识别出低觉醒状态，识别率达90.8%，可为提高警戒作业工作绩效提供一种可穿戴的智能装备。