80kt/a硫磺回收装置国产化设计

介绍了无在线炉硫回收工艺的基本原理、技术特点和催化剂使用情况。已投用的工业装置运行结果证明 ,用该工艺设计的硫磺回收装置 ,硫回收率和尾气净化度高 ,投资少 ,能耗低 ,流程简单 ,操作控制方便 ,社会效益和经济效益显著 ,适用于同类装置的新建和改扩建项目 ,市场前景广阔。     

改进SSR算法在人脸识别中的应用

为提高人脸检测中人脸验证的速度,在平方积分图像和图像窗口的灰度均值及方差快速计算基础上,对传统的SSR算法中人脸验证算法部分进行了改进。应用改进的算法,结合窗口灰度标准化的计算和平均人脸模板的取得,引入相关系数和平均偏差,加快了求解速度,克服了由于噪声点的存在对真实的候选脸图像漏检的情况。人脸检测实验证明应用改进的模板匹配算法的正确性.     

Bifurcation analysis for an SMIB power system with series capacitor compensation associated with sub-synchronous resonance

In this paper,an introduction to the bifurcation theory and its applicability to the study of sub-synchronous resonance (SSR) phenomenon in power system are presented. The continuation and bifurcation analysis software AUTO97 is adopted to investigate SSR for a single-machine-infinite-bus power system with series capacitor compensation. The investigation results show that SSR is the result of unstable limit cycle after bifurcation. When the system exhibits SSR, some complex periodical orbit bifurcations, such as torus bifurcation and periodical fold bifurcation, may happen with the variation of limit cycle. Furthermore, the initial operation condition may greatly influence the ultimate state of the system. The time-domain simulation is carried out to verify the effectiveness of the results obtained from the bifurcation analysis.     

Adaptive RTRL based neurocontroller for damping subsynchronous oscillations using TCSC

Modern interconnected electrical power systems are complex and require perfect planning, design and operation. Hence the recent trends towards restructuring and deregulation of electric power supply has put great emphasis on the system operation and control. Flexible AC transmission system (FACTS) devices such as thyristor controlled series capacitor (TCSC) are capable of controlling power flow, improving transient stability and mitigating subsynchronous resonance (SSR). In this paper an adaptive neurocontroller is designed for controlling the firing angle of TCSC to damp subsynchronous oscillations. This control scheme is suitable for non-linear system control, where the exact linearised mathematical model of the system is not required. The proposed controller design is based on real time recurrent learning (RTRL) algorithm in which the neural network (NN) is trained in real time. This control scheme requires two sets of neural networks. The first set is a recurrent neural network (RNN) which is a fully connected dynamic neural network with all the system outputs fed back to the input through a delay. This neural network acts as a neuroidentifier to provide a dynamic model of the system to evaluate and update the weights connected to the neurons. The second set of neural network is the neurocontroller which is used to generate the required control signals to the thyristors in TCSC. This is a single layer neural network. Performance of the system with proposed neurocontroller is compared with two linearised controllers, a conventional controller and with a discrete linear quadratic Gaussian (DLQG) compensator which is an optimal controller. The linear controllers are designed based on a linearised model of the IEEE first benchmark system for SSR studies in which a modular high bandwidth (six-samples per cycle) linear time-invariant discrete model of TCSC is interfaced with the rest of the system. In the proposed controller, since the response time is highly dependent on the number of states of the system, it is often desirable to approximate the system by its reduced model. By using standard Hankels norm approximation technique, the system order is reduced from 27 to 11th order by retaining the dominant dynamic characteristics of the system. To validate the proposed controller, computer simulation using MATLAB is performed and the simulation studies show that this controller can provide simultaneous damping of swing mode as well as torsional mode oscillations, which is difficult with a conventional controller. Moreover the fast response of the system can be used for real-time applications. The performance of the controller is tested for different operating conditions.     

一种新型的三相异步电动机保护电路设计介绍

文章介绍了三相异步电动机电源的相序接反,断相,三相电压不平衡的故障监测保护电路的电路结构及工作原理。     

网络流量监测服务器系统的研究

在电信企业的大型网络体系中,对网络数据流量的监测和控制已经为人们所关注。结合Flow Accounting Server(FAS)和Cabletron Traffic Accounting(CTA)管理系统,通过对LFAP协议的分析和研究,提出了对网络的流量和策略进行控制的方法,从而解决了大量的网络流 量监测任务。     

Gd0.8Sr0.2 CoO3-Sm0.2Ce0.80 O1.9复合阴极制备及性能研究

为探索适于中温条件下使用的固体氧化物燃料电池的阴极材料,用固相反应法制备了Gd0.8Sr0.2CoO3(GSC)阴极粉体,用X射线衍射考察了GSC的成相温度.采用丝网印刷法将GSC-(Sm2O3)0.1(CeO2)0.8(SDC)沉积在SDC电解质圆片上,制成对称阴极,在不同温度下烧结.用交流阻抗谱从500～750℃测量了GSC-SDC复合阴极和SDC电解质之间的界面电阻.结果表明,GSC-SDC复合阴极的界面电阻比GSC阴极降低了3～5倍;750℃时,GSC-SDC阴极的界面电阻仅为0.15Ω·cm2.     

饱和-非饱和非稳定渗流作用下岩质边坡稳定性分析

对岩质边坡在水位下降时坡体内的饱和—非饱和非稳定渗流和坡体稳定性进行了分析,渗流分析采用有限元法,坡体稳定分析采用有限元强度折减法。以塑性区位移突变作为边坡失稳判据,此时折减系数值即为坡体安全系数。以十里铺水库为例,对库岸岩体边坡进行了分析,并得出在水库水位降落影响下边坡的稳定安全系数随降落时间的增长而增大的结论。     

甘蓝型油菜SSR核心引物研究

为了确定一组适用于品种纯度鉴定和遗传多样性分析的SSR核心引物,以100份具有代表性的甘蓝型油菜品种（系）为研究材料对746对SSR引物进行筛选,综合考虑PIC（平均多态信息量）值大小、引物重复性、扩增带型清晰度、连锁群分布等因素,确定44对引物为甘蓝型油菜核心引物,其中20对引物为首选核心引物,24对引物为备选核心引物。20对首选核心引物每对可检测到3~9个多态性位点,PIC值介于0.56~0.80,共检测到102个位点,分布于11个连锁群上。随机抽取1对核心引物对一个杂交组合大田制种F1纯度进行鉴定,其鉴定结果与田间自然鉴定结果一致,并可同时鉴别出来源于父本及外来的混杂单株。将44对核心引物应用于品种的系谱分析和100份品种遗传多样性聚类分析,同样得到了很好的验证结果。该套SSR核心引物适用于甘蓝型油菜品种鉴定及遗传多样性研究。     

基于分支定界法的相控阵雷达事件调度算法

为解决相控阵雷达事件调度问题中调度成功率、时间偏移率与算法时效性三者之间的矛盾，本文提出一种基于分支定界法的调度算法；该算法首先在现有调度结果上调取所有可执行事件，即获得若干"节点"，多步递推后由多"层"节点形成若干条备选"分支"，扩大解空间范围，提高算法性能；然后通过"删减"操作删减掉收益较低分支，将解空间控制在一适当范围内，减小搜索盲目性，降低算法计算量.仿真实验表明，与基于综合优先级算法的调度结果相比，利用本文算法调度时调度成功率提升了52%；与基于时间指针算法的调度结果相比，本身算法时间偏移率降低了61%；与基于遗传算法的调度结果相比，本文算法调度耗时仅为前者1~2%.