模糊聚类分析用于断路器状态评估因素分类  被引量:13

Clustering Analysis in Condition Assessment Factor Classification of Circuit Breaker

在线阅读下载全文

作  者:张国钢[1] 李宇[1] 汤翔[1] 耿英三[1] 

机构地区:[1]西安交通大学电力设备电气绝缘国家重点实验室,西安710049

出  处:《高电压技术》2008年第2期350-354,共5页High Voltage Engineering

基  金:教育部科学技术研究重点项目资助(105158)~~

摘  要:为了使高压断路器工作状态的评估更准确可靠,提高其诊断精度,提出了采用模糊聚类分析方法以模糊综合评判过程中各评价因素的分类。该法首先提取各评价因素的特征,构造模糊相似矩阵和模糊等价矩阵,再通过选取不同阈值下的截集,进行动态聚类,建立层次模型,最后利用模糊层次分析法确定不同层次中评价因素的权重。以SF6高压断路器为例,给出的聚类分析过程表明,基于模糊聚类分析的因素分类方法合理有效。A method based on the fuzzy theory is introduced for condition assessment of high voltage circuit breaker. By this means, the condition affected factors are classified using the fuzzy cluster analysis. The process is in the fol lowing: First, the main factors for assessing the condition of the high voltage circuit breaker are selected and ab stracted, according to circuit breaker type such as SF6, oil and vacuum circuit breaker. Second, a fuzzy similar matrix is constructed using those factor items. Based on resolution structure of fuzzy equivalent matrix, a fuzzy equivalent matrix is worked out. Thirdly, dynamic clustering analysis is realized, with calculating sectional sets of the fuzzy equivalent matrix under different threshold conditions. Then a hierarchical model of fuzzy comprehensive con dition assessment for high voltage circuit breaker is made up. Finally, the weights of those factors are calculated by the method of the fuzzy analytical hierarchy process. The process of dynamic clustering, judgment set selecting and hierarchy of the factors calculating for SF6 high voltage circuit breaker are given in detail. Also, a sample of circuit breaker is analyzed to prove that assessment factors classification method of high voltage circuit breaker based on fuzzy cluster analysis is rational and effective.

关 键 词:模糊聚类分析 高压断路器 状态评估 因素分类 权重分配 模糊层次分析 

分 类 号:F224[经济管理—国民经济]

 

参考文献:

正在载入数据...

 

二级参考文献:

正在载入数据...

 

耦合文献:

正在载入数据...

 

引证文献:

正在载入数据...

 

二级引证文献:

正在载入数据...

 

同被引文献:

正在载入数据...

 

相关期刊文献:

正在载入数据...

相关的主题
相关的作者对象
相关的机构对象