通过物联网(the internet of things,IoT)终端对高压线路进行实时在线检测是非常重要的技术方法。传统的电流互感器在高压输电线上流过的电流较小时难以高效取电供后级物联网终端设备。针对该问题,提出了一种基于电磁互感自取电的恒压...通过物联网(the internet of things,IoT)终端对高压线路进行实时在线检测是非常重要的技术方法。传统的电流互感器在高压输电线上流过的电流较小时难以高效取电供后级物联网终端设备。针对该问题,提出了一种基于电磁互感自取电的恒压并联电流补偿方法,设计了补偿电路。通过对升压电路输出端的电流采样,来控制主副线圈回路的并联电流,实现高效取电,达到在高压线路微小电流情况下用电设备进行正常供电的需求。通过实验与实际应用证明,该设备在流经高压线路的电流微小时能够保持稳定对后级设备进行供电,为物联网终端设备的稳定运行提供了可靠的电源。展开更多
据国家电路部门统计,我国的线路电压等级高于110 k V以上的输电总长度近106km,且线路经过的地形复杂,故障不可避免会发生。文中介绍了通过物联网和GPRS技术进行无线远距离传输的高压输配电线路故障检测系统方案,该系统能实时监测输配电...据国家电路部门统计,我国的线路电压等级高于110 k V以上的输电总长度近106km,且线路经过的地形复杂,故障不可避免会发生。文中介绍了通过物联网和GPRS技术进行无线远距离传输的高压输配电线路故障检测系统方案,该系统能实时监测输配电线的运行状况,如:电流、温度等。并能实现远程报警和自动定位功能,使其能在1 min及时将故障点通知控制中心和管理人员。整个系统的检测终端结点和网关结点的能量采用高压输电线电磁线圈互感自取电技术,电源产品寿命无年限,使用时间较长。展开更多
In modern electromagnetic environment, radar emitter signal recognition is an important research topic. On the basis of multi-resolution wavelet analysis, an adaptive radar emitter signal recognition method based on m...In modern electromagnetic environment, radar emitter signal recognition is an important research topic. On the basis of multi-resolution wavelet analysis, an adaptive radar emitter signal recognition method based on multi-scale wavelet entropy feature extraction and feature weighting was proposed. With the only priori knowledge of signal to noise ratio(SNR), the method of extracting multi-scale wavelet entropy features of wavelet coefficients from different received signals were combined with calculating uneven weight factor and stability weight factor of the extracted multi-dimensional characteristics. Radar emitter signals of different modulation types and different parameters modulated were recognized through feature weighting and feature fusion. Theoretical analysis and simulation results show that the presented algorithm has a high recognition rate. Additionally, when the SNR is greater than-4 d B, the correct recognition rate is higher than 93%. Hence, the proposed algorithm has great application value.展开更多
Network forensics is a security infrastructure,and becomes the research focus of forensic investigation.However many challenges still exist in conducting network forensics:network has produced large amounts of data;th...Network forensics is a security infrastructure,and becomes the research focus of forensic investigation.However many challenges still exist in conducting network forensics:network has produced large amounts of data;the comprehensibility of evidence extracting from collected data;the efficiency of evidence analysis methods,etc.To solve these problems,in this paper we develop a network intrusion forensics system based on transductive scheme that can detect and analyze efficiently computer crime in networked environments,and extract digital evidence automatically.At the end of the paper,we evaluate our method on a series of experiments on KDD Cup 1999 dataset.The results demonstrate that our methods are actually effective for real-time network forensics,and can provide comprehensible aid for a forensic expert.展开更多
The Mars Advanced Radar for Subsurface and Ionosphere Sounding(MARSIS) onboard the Mars Express(MEX) spacecraft started to collect data of the Martian topside ionosphere from May,2005.By now a large amount of ionogram...The Mars Advanced Radar for Subsurface and Ionosphere Sounding(MARSIS) onboard the Mars Express(MEX) spacecraft started to collect data of the Martian topside ionosphere from May,2005.By now a large amount of ionograms has been obtained.It is important to extract vertical ionospheric information effectively from the ionograms for further study.In this paper a new method,Object Tracking Method(OTM),is proposed to automatically extract the ionospheric electron density profiles by computer.This method is based on three algorithms,namely the Hough transform,region growing segmentation algorithm and moving objects detection method from video sequences.In processing ionosphere echoes are treated as moving objects.The identification ratio of OTM for the MARSIS ionograms is estimated to be around 90%.展开更多
文摘通过物联网(the internet of things,IoT)终端对高压线路进行实时在线检测是非常重要的技术方法。传统的电流互感器在高压输电线上流过的电流较小时难以高效取电供后级物联网终端设备。针对该问题,提出了一种基于电磁互感自取电的恒压并联电流补偿方法,设计了补偿电路。通过对升压电路输出端的电流采样,来控制主副线圈回路的并联电流,实现高效取电,达到在高压线路微小电流情况下用电设备进行正常供电的需求。通过实验与实际应用证明,该设备在流经高压线路的电流微小时能够保持稳定对后级设备进行供电,为物联网终端设备的稳定运行提供了可靠的电源。
文摘据国家电路部门统计,我国的线路电压等级高于110 k V以上的输电总长度近106km,且线路经过的地形复杂,故障不可避免会发生。文中介绍了通过物联网和GPRS技术进行无线远距离传输的高压输配电线路故障检测系统方案,该系统能实时监测输配电线的运行状况,如:电流、温度等。并能实现远程报警和自动定位功能,使其能在1 min及时将故障点通知控制中心和管理人员。整个系统的检测终端结点和网关结点的能量采用高压输电线电磁线圈互感自取电技术,电源产品寿命无年限,使用时间较长。
基金Project(61301095)supported by the National Natural Science Foundation of ChinaProject(QC2012C070)supported by Heilongjiang Provincial Natural Science Foundation for the Youth,ChinaProjects(HEUCF130807,HEUCFZ1129)supported by the Fundamental Research Funds for the Central Universities of China
文摘In modern electromagnetic environment, radar emitter signal recognition is an important research topic. On the basis of multi-resolution wavelet analysis, an adaptive radar emitter signal recognition method based on multi-scale wavelet entropy feature extraction and feature weighting was proposed. With the only priori knowledge of signal to noise ratio(SNR), the method of extracting multi-scale wavelet entropy features of wavelet coefficients from different received signals were combined with calculating uneven weight factor and stability weight factor of the extracted multi-dimensional characteristics. Radar emitter signals of different modulation types and different parameters modulated were recognized through feature weighting and feature fusion. Theoretical analysis and simulation results show that the presented algorithm has a high recognition rate. Additionally, when the SNR is greater than-4 d B, the correct recognition rate is higher than 93%. Hence, the proposed algorithm has great application value.
基金supported by the National Natural Science Foundation of China under Grant No.60903166 and 61170262the National High-Tech Research and Development Plan of China under Grant Nos.2012AA012506+4 种基金Specialized Research Fund for the Doctoral Program of Higher Education of China under Grant No.20121103120032the Humanity and Social Science Youth Foundation of Ministry of Education of China under Grant No.13YJCZH065General Program of Science and Technology Development Project of Beijing Municipal Education Commission of China under Grant No.km201410005012the Research on Education and Teaching of Beijing University of Technology under Grant No.ER2013C24Open Research Fund of Beijing Key Laboratory of Trusted Computing
文摘Network forensics is a security infrastructure,and becomes the research focus of forensic investigation.However many challenges still exist in conducting network forensics:network has produced large amounts of data;the comprehensibility of evidence extracting from collected data;the efficiency of evidence analysis methods,etc.To solve these problems,in this paper we develop a network intrusion forensics system based on transductive scheme that can detect and analyze efficiently computer crime in networked environments,and extract digital evidence automatically.At the end of the paper,we evaluate our method on a series of experiments on KDD Cup 1999 dataset.The results demonstrate that our methods are actually effective for real-time network forensics,and can provide comprehensible aid for a forensic expert.
基金supported by the National Natural Science Foundation of China(Grant Nos. 10973031,2008AA12A210 and 2010AA122206)
文摘The Mars Advanced Radar for Subsurface and Ionosphere Sounding(MARSIS) onboard the Mars Express(MEX) spacecraft started to collect data of the Martian topside ionosphere from May,2005.By now a large amount of ionograms has been obtained.It is important to extract vertical ionospheric information effectively from the ionograms for further study.In this paper a new method,Object Tracking Method(OTM),is proposed to automatically extract the ionospheric electron density profiles by computer.This method is based on three algorithms,namely the Hough transform,region growing segmentation algorithm and moving objects detection method from video sequences.In processing ionosphere echoes are treated as moving objects.The identification ratio of OTM for the MARSIS ionograms is estimated to be around 90%.
