电力系统及其自动化学报2016，Vol.28Issue(11)：117-122,6.DOI:10.3969/j.issn.1003-8930.2016.11.020
邻域粗糙集与相关向量机相结合的变压器故障综合诊断模型
Comprehensive Fault Diagnosis Model of Transformers Based on Combination of Neighborhood Rough Set and Relevance Vector Machine
陈嘉霖 1段家华 1张明宇1
作者信息
- 1. 云南省能源投资集团有限公司，昆明 650021
- 折叠
摘要
Abstract
To deal with the issue of generalization ability affected by redundant information in the relevance vector ma⁃chine(RVM)based fault diagnosis model of transformers,this paper proposes a comprehensive fault diagnosis model based on the combination of neighborhood rough set(NRS)and RVM. First,neighborhood information and quick re⁃duction algorithm are employed to reduce the attribute reduction. Then,the dependence of conditional attribute on deci⁃sion attribute is used to acquire the attribute weight. Next,the feature vector set obtained after reduction and numeral⁃ization is input into the RVM for training. Finally,tests are conducted with test set. A case study shows that the diagno⁃sis rate with the proposed method is higher than the RVM model,which further indicates that NRS enhances the practi⁃cability and accuracy of RVM.关键词
邻域粗糙集/相关向量机/变压器/故障诊断/诊断精度Key words
neighborhood rough set(NBS)/relevance vector machine(RVM)/transformer/fault diagnosis/diagnosis accuracy分类
信息技术与安全科学引用本文复制引用
陈嘉霖,段家华,张明宇..邻域粗糙集与相关向量机相结合的变压器故障综合诊断模型[J].电力系统及其自动化学报,2016,28(11):117-122,6.
