中国电机工程学报2024，Vol.44Issue(15)：5886-5898,中插4,14.DOI:10.13334/j.0258-8013.pcsee.230475
一种数据库查询的多标签电能质量混合扰动识别与分类新方法
A New Multi-label Database Query Method for Combined Power Quality Disturbances Classification and Recognition
摘要
Abstract
This paper proposes a new multi-label database query method for combined power quality disturbances(PQDs)recognition and classification,aiming at the problems of the complexity of combined PQDs and the insufficient accuracy of current classification.This new method can be used to recognize combined PQDs more scientifically and accurately,which can provide powerful decision-making assistance for PQ management and disturbance event accountability.First,this method employs the proposed feature extraction method based on the tunable Q-factor wavelet transform(TQWT)and time-varying root mean square(RMS)to effectively extract the fundamental time domain features from the PQDs,which is an effective way to overcome the current difficulties of insufficient accuracy in extracting fundamental amplitude features.Next,the proposed frequency-domain characteristic curve segmentation method is used to extract the high-frequency characteristic curve of the PQDs effectively.Then,the fundamental frequency amplitude feature database and the high-frequency characteristic curve database are established.The multi-label database query with fast dynamic time warping(DTW)is used to classify the combined PQDs effectively.The simulation results show that the new method has the following advantages:It is hardly affected by the fundamental frequency deviations within the range specified in the GB/T standard,and it has not only good noise tolerance capability,but also high classification accuracy for 27 kinds of PQDs,including single,double,triple,and quadruple disturbances.Finally,its effectiveness is further verified by the actual disturbance data collected from the power grid.关键词
混合扰动多标签分类/可调Q因子小波变换/时变均方根/特征曲线分割/快速动态时间规整Key words
multi-label classification of combined disturbances/Q-factor wavelet transform/time-varying root mean square/segmentation of characteristic curve/fast dynamic time warping分类
信息技术与安全科学引用本文复制引用
王燕,李雨婕,卞安吉,骆玉深,江浙,曹浩敏..一种数据库查询的多标签电能质量混合扰动识别与分类新方法[J].中国电机工程学报,2024,44(15):5886-5898,中插4,14.基金项目
四川省科技创新苗子工程项目(2022027) （2022027）
西南民族大学中央高校基本科研业务费专项资金项目(ZYN2022091). Project Supported by Science and Technology Innovation Miaozi Program of Sichuan Province(2022027) （ZYN2022091）
Fundamental Research Funds for the Central Universities,Southwest Minzu University(ZYN2022091). （ZYN2022091）
