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文章摘要
基于深度信息融合的小电流接地故障选线
Fault Line Detection Based on Depth Information Fusion for Small Current Grounding System
Received:June 11, 2015  Revised:December 04, 2015
DOI:
中文关键词: 信息增益度  故障选线 最小二乘支持向量机  信息融合
英文关键词: Information  Gain Fault  Line Selection  LSSVM Information  Fusion
基金项目:
Author NameAffiliationE-mail
Feng XiaoHong Power supply company of jiangsu haian jiangsu haian china jdbh2001@163.com 
ChenBoBo* School of Information and Electrical Engineering, China University of Mining and Technology 1553321327@qq.com 
ChuYaNan Power supply company of jiangsu haian jiangsu haian china  
ChenKui School of Information and Electrical Engineering, China University of Mining and Technology  
WangAiDong Power supply company of jiangsu haian jiangsu haian china  
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中文摘要:
      基于信息融合技术的小电流接地故障选线方法当信息融合效率低时,将直接影响接地选线的准确性。分别利用傅里叶变换(FFT)和经验模态分解(EMD)对稳态和暂态的零序分量特征进行分析,通过建立故障测度函数,计算出线路故障测度;利用信息增益度,建立各种选线方法的故障测度;利用线路和方法故障测度得到最终的样本故障测度。把样本故障测度作为特征输入量,利用单纯形法(SM)优化参数的最小二乘支持向量机(LSSVM)算法进行深度信息融合选线。仿真结果表明上述方法应用于选线中具有很高的准确率和灵敏度。
英文摘要:
      When the fusion efficiency is low, the method based on information fusion technology will directly affect the accuracy of the grounding line selection . Respectively using EEMD and FFT to analyze the zero-sequence component of steady-state and transient, this paper sets up faulty measurement function to calculate fault measures of feeders and establishes fault measures of different methods based on information gain,finally, sample fault measures are founded by fusing the two fault measures. Then the depth information fusion line selection is conducted by using the least squares support vector machine (LSSVM) of the simplex optimum-seeking algorithm and the information gain degree with the sample falut measures as characteristic input. Simulation results show that the above method is of high accuracy and sensitivity in fault line selection.
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