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基于层次分析法和粗糙集的变压器状态评估研究 被引量:14

Research on Assessment of Transformer State Using Analytic Hierarchy Process and Rough Set Theory
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摘要 针对变压器状态单一评价方法存在的不足和影响变压器性能的状态量错综复杂的特征,建立基于层次分析法和粗糙集的变压器状态评估模型。对变压器部件、状态量进行层次结构划分,借鉴专家经验并以层次分析法求得各部件、状态量的主观权重;结合变压器测试数据,运用粗糙集理论分析出各部件、状态量的客观权重;将主、客观权重进行优化组合,以反映各部件、状态量在变压器综合状态评估的权值。运用该模型对两台不同类型变压器的检修数据进行分析并得出变压器状态评价结果,将该结果与实际变压器检修状况对比,结果表明,此模型具有全面准确地评价变压器状态的能力。 In view of the problems of single transformer condition evaluation method and the complicated factors thataffected the performance of transformer,a state assessment method of transformer based on AHP(analytic hierarchyprocess,AHP)method and rough set theory is proposed. Combined with the experience of experts,the AHP methodis used to obtain the subjective weights of the components and state quantities divided by the hierarchical structure;By the test data of transformer,it is adopted to analysis the objective weight of each part and state quantities by roughset theory,the optimized combination weights,which is the combinatorial optimization of subjective and objectiveweights,reflected in the proportion of the parts,state quantities of the running state of transformers. The model is applied to analyze the maintenance data of two different types of transformers and the results are compared with the actual transformer maintenance status,it has proved that this model has the ability to evaluate the transformer statuscomprehensively and accurately.
作者 彭道刚 陈跃伟 范俊辉 钱玉良 PENG Daogang;CHEN Yuewei;FAN Junhui;QIAN Yuliang(Engineering Research Center of Intelligent Management and Control for Power Process(School of Automation Engineering,Shanghai University of Electric Power),Shanghai 200090,China;State Grid Corporation of Nanping Power Supply Company,Fujian Nanping 353000,China)
出处 《高压电器》 CAS CSCD 北大核心 2019年第7期150-157,共8页 High Voltage Apparatus
基金 上海市“科技创新行动计划”社会发展领域项目(16DZ1202500) 上海市青年科技英才扬帆计划(16YF1404700) 上海市科学技术委员会工程技术研究中心项目资助(14DZ2251100)~~
关键词 层次分析法 粗糙集 变压器状态评价 主、客观权重 权值优化组合 analytic hierarchy process method rough set theory assessment of transformer state subjective&objective weight optimized combination weights
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