Deep Analysis of Power Equipment Defects Based on Semantic Framework Text Mining Technology

查看全文 作　　者：Huifang [1]Wang;Jing [1]Cao;Dongyang [2]Lin

机构地区：[1]Electrical Engineering Department,Zhejiang University,Hangzhou 310058,China;[2]State Grid Jiangsu Electric Power Engineering Consulting Co.,Ltd.,Nanjing 210000,China

出　　处：《CSEE Journal of Power and Energy Systems》索引2022年第8卷第4期,共8页

摘　　要：Defect factors and their relevant rules can be analyzed in depth by processing defect records which are often expressed in the form of text data.However,considering that defect text consists of both structured and unstructured data,it is necessary to excavate structured information from unstructured data.In this paper,a text mining method based on semantic framework technology is introduced to transform unstructured defect description into structured information such as components and defect attributes.Then,a deep analyzing model of a power equipment defect is established,which provides a scheme of defect mining based on historical defect texts.Case studies prove that the proposed deep analysis method has a guiding significance for equipment upgrading,selection and maintenance. 关键词：Age curve defect analysis defect rate factor study power equipment text mining

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Deep Analysis of Power Equipment Defects Based on Semantic Framework Text Mining Technology

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引证文献(4)

耦合文献(353)

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