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计算机系统应用英文版:2014,23(9):191-197
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基于模糊综合支持向量机的特高压变电站二次设备状态评估
(1.兰州交通大学 自动化与电气工程学院, 兰州 730070;2.甘肃省电力公司检修公司, 兰州 730070)
Status Assessment of UHV Substation Secondary Equipment Based on Fuzzy Comprehensive Support Vector Machine Method
(1.School of Automation & Electrical Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China;2.State Grid Gansu Electric Power Company, Lanzhou 730070, China)
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Received:January 07, 2014    Revised:February 24, 2014
中文摘要: 针对超高压变电站二次设备状态检修科学依据不足的问题,给出了一种基于模糊综合支持向量机的二次设备状态评估模型. 对综合自动化系统上传的在线告警信息和检修报告中的离线信息进行了分析,采用模糊综合分析实现对各种评估因素的有效利用和信息提取,在此基础上运用改进型SVM 对二次设备状态进行评估.在SVM 评估过程中,对三种不同核函数进行了实验分析,选取RBF 作为模型的核函数. 实验结果证明,模糊综合支持向量机评估模型的提高了二次设备状态评估正确率.
Abstract:According to the scientific basis insufficient in the maintenance of secondary equipment of transformer substation, a status assessment model based on fuzzy comprehensive support vector machine (FC-SVM) is proposed. The online alarm information uploaded from integrated automation system and offline information in maintenance report is analyzed, an effective utilization and information extraction of various assessment factors is achieved by using fuzzy comprehensive assessment method (FCA), based on which, the secondary equipment status is assessed via SVM. Experiment analysis is carried out on four different kernel functions and radial basis function (RBF) is selected as the kernel function for the proposed model, finally. Experimental results show that the status assessment accuracy of secondary equipment is improved by using FC-SVM.
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基金项目:国家自然科学基金(61165006)
引用文本:
马博,董海鹰,任伟.基于模糊综合支持向量机的特高压变电站二次设备状态评估.计算机系统应用,2014,23(9):191-197
MA Bo,DONG Hai-Ying,REN Wei.Status Assessment of UHV Substation Secondary Equipment Based on Fuzzy Comprehensive Support Vector Machine Method.COMPUTER SYSTEMS APPLICATIONS,2014,23(9):191-197