高电压技术2024，Vol.50Issue(5)：1913-1922,10.DOI:10.13336/j.1003-6520.hve.20230992
基于声阵列时空关联特征融合的不平衡局部放电类型识别方法
Pattern Recognition of Partial Discharge Using Imbalanced Acoustic Array Data Based on Spatial Correlation and Temporal Correlation Feature Fusion Method
摘要
Abstract
Microphone array can detect partial discharge(PD)of power equipment in a non-contact and flexible way.However,existing methods lack the consideration of data characteristics of acoustic array,and the researches on identifi-cation of PD type are insufficient.Considering the correlation and imbalanced distribution features,this paper firstly analyzes the temporal and spatial correlation characteristics of microphone array data.Secondly,based on one-dimensional convolutional neural network and"squeeze-and-excitation"correlation extraction method,a PD pattern recognition model based on spatial and temporal correlation feature fusion strategy is proposed.Finally,the loss function adjustment method and data distribution adjustment method are used to deal with the imbalance between different PD classes.Simulations show that,compared with the methods in which the correlations are not taken into consideration,the methods proposed in this paper enhance both the precision and recall by more than 12%.Compared with the methods in which the data imbalance is not taken into consideration,the methods improve the precision and recall by over 60%,re-spectively.These results affirm the essential need to consider both correlation and imbalance characteristics in acoustic array based PD recognition.关键词
声阵列/局部放电/时空关联性/特征融合/不平衡数据Key words
acoustic sensor array/partial discharge/spatial-temporal correlation/feature fusion/imbalanced data引用本文复制引用
王红霞,王波,张嘉鑫,尚宇炜,周莉梅,刘畅..基于声阵列时空关联特征融合的不平衡局部放电类型识别方法[J].高电压技术,2024,50(5):1913-1922,10.基金项目
国家电网有限公司科技项目(5400-202155497A-0-5-ZN).Project supported by Science and Technology Project of SGCC(5400-202155497A-0-5-ZN). （5400-202155497A-0-5-ZN）
