大用户直接交易合同执行风险评估

目前我国正稳步推进电力市场改革,大用户直接交易作为其中重要的形式有着可再生能源大量参与、交易电量巨大、电源分布广、传输距离远等特点,其交易的可靠性对电力系统的稳定性便有了十分重要的影响,因而必须对供需两侧用户交易进行有效的风险评估,对风险较大的影响因素进行合理的管控。大用户直接交易涉及供需两侧及诸多可能存在的风险因素,运用层次分析法对进行评价,主要从自然风险、准入风险、信用风险、交易风险、结算风险5个方面构建风险评价指标体系,以及对应的17个二级评价指标,并将风险因素进行评级,确定各自权重并检验一致性,最后对严重风险进行重点防范。结果表明,层次分析法可以兼顾主客观因素,确定各评价指标相对权重,计算风险指标对各等级风险水平的隶属度,实现定性与定量分析相结合,使风险评估的结果更加科学准确。     

U形高筋整体壁板激光诱导精密成形实验研究

目的 提高U形高筋整体壁板激光诱导成形精度。方法 根据U形高筋整体壁板特点,首先初步确定成形扫描策略,然后采用几何分析方法计算不同扫描位置成形后的理论变形量,并根据理论变形量对扫描策略和成形工艺参数进行优化。随后开展试验研究。同时利用在线可视化测量手段,对U形高筋壁板的变形量进行测量。结果 扫描道次数和激光器功率大小对U形高筋整体壁板成形精度影响很大,随着扫描次数和激光器功率的增加,变形量随之增大。结论 成形后板材的尺寸误差不大于0.4%,实现了U形高筋整体壁板的高精密成形。     

Research on Extraction Method of Coastal Aquaculture Areas on High Resolution Remote Sensing Image based on Multi-features Fusion

Coastal aquaculture areas are the important marine disaster bearing body,it is of great significance to carry out the research about automatically extraction aquaculture areas based on remote sensing for master basic information of coastal areas,mitigation and prevention of marine disasters.Used Gaofen-2 images for experimental data,and chose Dongshan Island sea in Fujian province as the experimental area,on the basis of analyzed the spectral characteristics of the aquaculture areas,construct feature index to extract spectral feature,used gray-level co-occurrence matrix method to extract the texture feature of the aquaculture areas,fused spectral features and texture features after feature selection,then used Otsu method to determine the threshold for raft culture area and fishing cage culture area,to achieve high precision intelligent extraction and classification for coastal aquaculture areas.The extraction accuracy of the raft culture area is more than 80%,and the extraction precision of the fish cage culture area is above 90%,and the overall extraction precision of the culture area is up to 87%.     

北斗三号基本系统空间信号质量评估

全球卫星导航系统(GNSS)空间信号(SIS)质量直接影响了用户使用性能。北斗三号卫星不同于北斗二号卫星,将继续播发北斗二号老信号,同时新增播发B1C, B2a等新信号,多频多信号多分量的信号体制较北斗二号更为复杂,对导航卫星信号质量控制提出了较大挑战。2018年底北斗系统完成了18颗卫星组网,完成北斗三号基本系统建设并开始提供全球服务,有必要对北斗三号在轨卫星空间信号质量进行量化评估。传统空间信号质量评估方法侧重于单项的定性评估,而针对北斗三号复杂的信号体制,缺乏系统的、定量的分析结果。该文对标北斗系统接口控制文件(ICD),从功率特性、频域特性、时域特性、相关域特性和信号一致性等方面研究了不同参数配置对评估结果的影响,形成了一套面向新型调制方式和多频多分量复用信号的量化评估方法。基于40 m大口径天线的空间信号质量评估系统,对18颗MEO卫星进行了长时间监测跟踪和数据采集,首次对北斗三号卫星空间信号质量进行了全面量化评估。结果表明：北斗三号卫星空间信号质量良好,18颗MEO卫星一致性较好,符合ICD指标要求,可满足服务区内用户需求;评估方法可用于对后续导航卫星空间信号质量的量化评估。     

互联网通信中信息隐藏技术的应用分析

在现代科学技术快速发展的背景下,我国已全面进入技术信息化时代,互联网、计算机等技术对社会发展产生了深刻的影响。现阶段,互联网已经成为主要的通信方式,其能高效传输大量的信息,但互联网具有高度的开放性,为了确保信息的安全性,需要加强对信息隐藏技术的应用,确保重要信息在传输过程中的安全性。文中分析了信息隐藏技术在互联网通信中的应用,并结合实践经验总结了一些措施,希望对相关人员有所帮助。     

卫星在轨运行视景仿真

针对卫星在轨运行系统演示的需要,将建模与仿真技术引入视景演示系统联邦成员,提出了基于HLA的卫星在轨运行视景演示系统,开发相应的联邦成员。利用卫星在轨运行仿真系统的总体方案,设计了视景演示系统的总体结构;引入了先进视景仿真软件Creator和Vega Prime对卫星在轨运行仿真系统中视景仿真联邦成员进行可视化仿真和建模实现,建立了卫星和星空恒星模型,可以用OpenGL的星空背景加速实现;最后结合HLA、OpenGL和Vega Prime建立仿真框图。仿真结果证明,设计的仿真系统满足系统真实的实时性、准确性要求,具有良好的沉浸感和较高的可信性。     

遥感图像中油罐目标精确定位与参数提取

目的 浮动顶油罐是遥感图像中具有圆形特征的典型人造目标,其高精度定位与参数提取问题是一类代表性的应用问题,针对该问题,传统的基于圆形特征的变换域提取方法鲁棒性差,参数选择需要不断手动调整;基于深度学习的方法利用对已有标注图像的训练求解网络参数,提高了自动化程度,但对于圆形目标而言,覆盖圆周需要较大的感受野,这对应较大的网络结构,随之带来细节信息缺失或参数量、运算量增大的问题。本文针对油罐的定位与参数提取问题,将传统特征提取与深度学习结合,提出了一种计算量小、精度高的方法。方法 基于快速径向对称变换（fast radial symmetry transform,FRST）后的变换域数据及原始数据构建了卷积神经网络（convolutional neural networks,CNN）,给出了训练过程及参数选择,有效地将圆形特征的先验引入深度学习过程,计算复杂度低,用较少层的网络实现了高精度的定位。结果 基于SkySat数据的实验表明,该方法比单纯基于深度学习的方法在相同网络量级上精度得到了有效提高,预测误差平均降低了17.42%,且随着网络深度的增加,精度仍有明显提高,在较浅层次网络中,预测误差平均降低了19.19%,在较深层次网络中,预测误差平均降低了15.66%。结论 本文针对油罐遥感图像定位与参数提取问题,提出了一种基于变换域特征结合深度学习的方法,有效降低了计算量,提升了精度和稳定性。本文方法适用于油罐等圆形或类圆形目标的精确定位和参数提取。     

Moving-window extended Kalman filter for structural damage detection with unknown process and measurement noises

The extended Kalman filter (EKF), as a popular tool for optimally estimating system state from noisy measurement, has been used successfully in various areas over the past several decades. However, classical EKF has several limitations when applied to structural system identification; thus, researchers have proposed a number of variations for this method. The current study focuses on using EKF for real-time system identification and damage detection in civil structures. An improved EKF approach, called moving-window EKF (MWEKF), is proposed in this paper after a discussion on the problems associated with the application of classical EKF in time-variant systems. The proposed approach uses the moving-window technique to estimate several statistical properties. MWEKF is more robust and adaptive in structural damage detection compared with classical EKF because of the following reasons: (1) it is insensitive to the selection of the initial state vector; (2) it exhibits more accurate system parameter identification; and (3) it is immune to the inaccurate assumption of noise levels because measurement and process noise levels are estimated in this approach. The salient features of MWEKF are illustrated through numerical simulations of time-variant structural systems and an experiment on a three-story steel shear building model. Results demonstrate that MWEKF is a robust and effective tool for system identification and damage detection in civil structures.     

A collaborative calculation on real-time stream in smart cities

In the smart cities, the travel-time is a typical business calculation to monitor and control the traffic congestions. But it still faces challenges on real-time stream due to the limitation of latency and accuracy. In this paper, we propose a collaborative approach for travel-time calculation on stream of recognized data of vehicles. Compared with other types of sensory data in urban roads, the recognized data of vehicles has wider coverage, finer interval and more exact locality. Our approach continuously achieves both factual and predictive values, and consists of two-step spatio-temporal parallelism on real-time data and Bayes prior rules mining on historical data. It can be analyzed theoretically for its low latency with high accuracy, and has been implemented on Apache Storm correlated with Hadoop MapReduce. Through exhaustive experiments on simulated and real data, our approach holds millisecond-level latencies steadily on high speed stream with nearly linear scalability, and keeps the accuracy above 80% for prediction.     

基于清洁能源价值分析的消纳框架研究

清洁能源消纳机制的设计,需要基于清洁能源本身的特点和价值。从清洁能源的全面价值分析出发,设计了清洁能源消纳框架,分析了其发展路径,并提出了现阶段的清洁能源省间交易品种建议。指出清洁能源的价值突出体现在其能源价值、环保价值和波动性负价值,对这3个核心价值的处理方式,构成了清洁能源消纳框架。根据对以上3个核心价值的不同处理方式,清洁能源消纳体系的发展可以分为4个阶段,当前正处于第2阶段。在当前已有的清洁能源市场交易品种基础上,设计了清洁能源省间交易品种,建议加强短期临时性交易品种,探索辅助服务交易和一般现货交易。