| 基于多源信息融合的电网故障诊断方法研究 |
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| 引用本文： | 高振兴,郭创新,俞斌,骆玉海,彭明伟,杨健.基于多源信息融合的电网故障诊断方法研究[J].电力系统保护与控制,2011,39(6):17-23. |
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| 作者姓名： | 高振兴 郭创新 俞斌 骆玉海 彭明伟 杨健 |
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| 作者单位： | 1.浙江大学电气工程学院，浙江 杭州 310027;2.烟建集团有限公司，山东 烟台 264000;3.浙江省电力设计院，浙江 杭州 310027;4.上海市电力公司市区供电公司，上海 200080 |
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| 基金项目： | 国家自然科学基金（50677062）；新世纪优秀人才支持计划资助（NCET-07-0745）；浙江省自然科学基金资助（R107062）；国家863计划（2008AA05Z210）；教育部博士点基金（20090101110058） |
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| 摘 要： | 考虑到电力系统自动化水平及通信、广域测量技术的发展，提出了一种综合SCADA开关量、故障录波器电气量及WAMS系统电气量的多源信息融合电网故障诊断方法。该方法将蕴含故障信息的电气量分析与开关量诊断相结合，对电网故障采集的电气量通过小波能量分析提取故障特征，采用蕴含时序贝叶斯网络对保护、断路器开关量进行故障推理，定义了能量畸变故障度、能量故障度、改进RBF神经网络故障度及时序贝叶斯故障度衡量线路故障程度，并作为证据体采用改进D-S证据理论进行信息融合，进而通过模糊C-均值聚类方法给出故障诊断决策。PSCAD
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| 关 键 词： | 故障诊断 小波能量谱 改进RBF神经网络 时序贝叶斯网络 改进D-S理论 信息融合 FCM |
Study of a fault diagnosis approach for power grid with information fusion based on multi-data resources |
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| GAO Zhen-xing,GUO Chuang-xin,YU Bin,LUO Yu-hai,PENG Ming-wei,YANG Jian.Study of a fault diagnosis approach for power grid with information fusion based on multi-data resources[J].Power System Protection and Control,2011,39(6):17-23. |
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| Authors: | GAO Zhen-xing GUO Chuang-xin YU Bin LUO Yu-hai PENG Ming-wei YANG Jian |
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| Affiliation: | GAO Zhen-xing1,GUO Chuang-xin1,YU Bin1,LUO Yu-hai2,PENG Ming-wei3,YANG Jian4(1.College of Electrical Engineering,Zhejiang University,Hangzhou 310027,China,2.Yanjian Group Co.,Ltd,Yantai 264000,3.Zhejiang Electric Power Design Institute,4.Shanghai Electric Power Company,Shanghai 200080,China) |
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| Abstract: | Considering the development of power system automation and communications and wide area measurement technology,this paper presents a fault diagnosis method for power grid with information fusion based on multi-data resources which contain the switching-status data from SCADA and continuous-time data derived from fault recorder and WAMS.Based on electrical value analysis with fault information and switch value diagnosis,this method employs the wavelet energy analysis to extract features from the continuous-t... |
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| Keywords: | fault diagnosis wavelet energy spectrum improved RBF networks Bayesian networks with temporal order improved D-S theory information fusion FCM |
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