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作 者:刘东超[1] 林语[1] 原辉 王帅 姜敏 俞华 李海涛[1] LIU Dongchao;LIN Yu;YUAN Hui;WANG Shuai;JIANG Min;YU Hua;LI Haitao(NR Electric Co.,Ltd.,Nanjing 211102,China;State Grid Shanxi Electric Power Company Electric Power Research Institute,Taiyuan 030001,China)
机构地区:[1]南京南瑞继保电气有限公司,江苏南京211102 [2]国网山西省电力公司电力科学研究院,山西太原030001
出 处:《中国电力》2020年第12期159-166,197,共9页Electric Power
基 金:国家电网有限公司科技项目(第三代智能变电站辅助系统研究,520530180015)。
摘 要:针对单一局部放电特征辨析老化信息量存在精度不足的问题,提出一种基于局部放电灰度纹理特征与油气特征的D-S证据融合识别方法,对油纸绝缘老化状态进行分析。首先,通过试验构造人工油纸绝缘内部气隙模型,模拟变压器内部实际运行环境,采集油纸绝缘7个老化层级的局部放电信号及油中气体含量,提取各老化层级的灰度纹理特征、统计特征及油气特征,利用支持向量机进行识别。将灰度纹理特征和油气特征的识别结果输入到D-S证据融合框架中进一步识别分析,识别结果与单一特征及其他两两特征融合结果比较。试验结果表明:基于灰度纹理特征与油气特征的D-S证据融合方法对油纸绝缘老化状态的识别效果更佳。Aiming at the problem of insufficient precision of aging information obtained by single partial discharge(PD) feature discrimination, a D-S evidence fusion recognition method based on PD gray texture and oil-gas features is proposed to analyze the aging state of oil-paper insulation. Firstly, an air gap model of artificial oil-paper insulation is constructed through experiments to simulate the actual operation environment inside the transformer. Next, the PD signals of seven aging levels of oil-paper insulation and the corresponding gas content in oil are collected. Then, the gray texture features, statistical features and oil-gas features of each aging level are extracted, and subsequently identified using the support vector machine. The identification results of gray texture features and oil-gas features are then input into the D-S evidence fusion framework for further recognition and analysis. Finally, the recognition results are compared with the single feature and other two-feature fusion results. The experimental results show that the D-S evidence fusion method based on gray texture feature and oil-gas feature can better identify the aging state of oil-paper insulation.
关 键 词:局部放电 灰度纹理特征 油气特征 D-S证据融合
分 类 号:TM855[电气工程—高电压与绝缘技术]
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