中国电机工程学报2017，Vol.37Issue(11)：3099-3107,9.DOI:10.13334/j.0258-8013.pcsee.161083
考虑小波奇异信息与不平衡数据集的输电线路故障识别方法
Method for Fault Type Identification of Transmission Line Considering Wavelet Singular Information and Unbalanced Dataset
摘要
Abstract
In view of unbalanced dataset during fault type identification of transmission line,a fault type identification technique based on wavelet singular information and improved synthetic minority over-sampling technique (SMOTE) was proposed.Firstly,unbalanced fault dataset of transmission line was established in PSCAD/EMTDC.Wavelet singular values of phase current fault component and zero-sequence current fault component were extracted as feature parameters based on stationary wavelet transform (SWT) and singular value decomposition (SVD).Furthermore,improved SMOTE algorithm was used to adjust the imbalance of dataset through random interpolation and resample in the vicinity of minority class center.Then,the support vector machine classifiers were trained by optimized dataset,to classify and identify 10 fault types of transmission line under various fault condition.Result of simulation indicates that the proposed method can effectively improve the identification ability of minority class and identification accuracy of classification algorithm under the condition of unbalanced sample dataset.It has better generalization performance and stronger robustness,and it is suitable for various classification algorithms.关键词
输电线路/故障类型识别/平稳小波变换/奇异值分解/不平衡数据集/过采样/支持向量机Key words
transmission lines/fault type identification/stationary wavelet transform/singular value decomposition/unbalanced dataset/over-sample/support vector machine分类
信息技术与安全科学引用本文复制引用
黄建明,李晓明,瞿合祚,张礼得..考虑小波奇异信息与不平衡数据集的输电线路故障识别方法[J].中国电机工程学报,2017,37(11):3099-3107,9.基金项目
国家自然科学基金项目(51277134).Project Supported by National Natural Science Foundation of China (51277134). （51277134）
