基于IIS5．1服务器和ASP．NET2．0开发平台实现对IP网络数据质量分析仪的远程控制。利用ASP．NET2．0 AJAX Extensions和Office Web Components来满足实时更新测试数据，动态显示测试结果的设计要求。应用结果表明其具有良好的性能和实...基于IIS5．1服务器和ASP．NET2．0开发平台实现对IP网络数据质量分析仪的远程控制。利用ASP．NET2．0 AJAX Extensions和Office Web Components来满足实时更新测试数据，动态显示测试结果的设计要求。应用结果表明其具有良好的性能和实用性。展开更多
基于IP的语音传输(Voice over Internet Protocol,VoIP)技术对语音信号进行数字化处理,再转换为网际互连协议(Internet Protocol,IP)数据包,并进行传输,以达到在IP网络进行语音通信的目的。文章借助华为技术有限公司eNSP平台搭建了网络...基于IP的语音传输(Voice over Internet Protocol,VoIP)技术对语音信号进行数字化处理,再转换为网际互连协议(Internet Protocol,IP)数据包,并进行传输,以达到在IP网络进行语音通信的目的。文章借助华为技术有限公司eNSP平台搭建了网络拓扑模拟VoIP话音网络,利用华为的网络质量分析(Network Quality Analysis,NQA)技术测试网络并分析结果。展开更多
Power Quality (PQ) combined disturbances become common along with ubiquity of voltage flickers and harmonics. This paper presents a novel approach to classify the different patterns of PQ combined disturbances. The cl...Power Quality (PQ) combined disturbances become common along with ubiquity of voltage flickers and harmonics. This paper presents a novel approach to classify the different patterns of PQ combined disturbances. The classification system consists of two parts, namely the feature extraction and the automatic recognition. In the feature extraction stage, Phase Space Reconstruction (PSR), a time series analysis tool, is utilized to construct disturbance signal trajectories. For these trajectories, several indices are proposed to form the feature vectors. Support Vector Machines (SVMs) are then implemented to recognize the different patterns and to evaluate the efficiencies. The types of disturbances discussed include a combination of short-term dis-turbances (voltage sags, swells) and long-term disturbances (flickers, harmonics), as well as their homologous single ones. The feasibilities of the proposed approach are verified by simulation with thousands of PQ events. Comparison studies based on Wavelet Transform (WT) and Artificial Neural Network (ANN) are also reported to show its advantages.展开更多
文摘基于IP的语音传输(Voice over Internet Protocol,VoIP)技术对语音信号进行数字化处理,再转换为网际互连协议(Internet Protocol,IP)数据包,并进行传输,以达到在IP网络进行语音通信的目的。文章借助华为技术有限公司eNSP平台搭建了网络拓扑模拟VoIP话音网络,利用华为的网络质量分析(Network Quality Analysis,NQA)技术测试网络并分析结果。
基金Project (No. 50437010) supported by the Key Program of the Na-tional Natural Science Foundation of China
文摘Power Quality (PQ) combined disturbances become common along with ubiquity of voltage flickers and harmonics. This paper presents a novel approach to classify the different patterns of PQ combined disturbances. The classification system consists of two parts, namely the feature extraction and the automatic recognition. In the feature extraction stage, Phase Space Reconstruction (PSR), a time series analysis tool, is utilized to construct disturbance signal trajectories. For these trajectories, several indices are proposed to form the feature vectors. Support Vector Machines (SVMs) are then implemented to recognize the different patterns and to evaluate the efficiencies. The types of disturbances discussed include a combination of short-term dis-turbances (voltage sags, swells) and long-term disturbances (flickers, harmonics), as well as their homologous single ones. The feasibilities of the proposed approach are verified by simulation with thousands of PQ events. Comparison studies based on Wavelet Transform (WT) and Artificial Neural Network (ANN) are also reported to show its advantages.
