基于卡尔曼滤波与MUSIC算法的传感阵列定向方法  

Directional Identification of Sensor Arrays Based on Kalman Filter and MUSIC Algorithms

作　　者：刘东甲 陶雄俊 王安军 郑全福 罗林根[2] LIU Dong-jia;TAO Xiong-jun;WANG An-jun;ZHENG Quan-fu;LUO Lin-gen(Kunming Bureau of Ultra High Voltage Transmission Company of China Southern Power Grid Co.,Ltd.,Kunming 650217,China;School of Electric Information and Electrical Engineering,Shanghai Jiao Tong University,Shanghai 200240,China)

机构地区：[1]中国南方电网有限责任公司超高压输电公司昆明局,云南昆明650217 [2]上海交通大学电子信息与电气工程学院,上海200240

出　　处：《水电能源科学》2024年第9期217-220,共4页Water Resources and Power

基　　金：中国南方电网有限责任公司超高压输电公司科技项目(0109002023030103SJ00006)。

摘　　要：对局放源信号的准确测量与有效识别是局部放电检测、定位及分析的关键。受电磁传感器方向特性灵敏度局限,现有基于到达角(AOA)定位的局部放电定位方法主要运用于声音信号。为此,提出一种卡尔曼滤波算法与多信号分类器(MUSIC)算法相结合的特高频传感阵列定向方法,即首先采用卡尔曼滤波算法能够有效处理电磁幅值信号,减小信号波动性及测量误差,大大提升信号测量精度;然后针对单一传感器建立了传感器方向性的参考矩阵,对任意来波信号使用MUSIC算法进行数据匹配,从而得到精确的来波方向;最后经过试验验证,所提算法可将传感器阵列的方向识别结果误差减小至5°以内,提升了测量精度。Accurate measurement and identification are crucial parts of partial discharge detection,localization,and analysis.Limited by the sensitivity of electromagnetic sensor directional characteristics,the existing partial discharge localization methods based on angle of arrival(AOA)localization are mainly based on sound signals.This article proposes an ultra high frequency sensing array localization method combining the Kalman filtering algorithm and MUSIC(Multiple Signal Classification).Firstly,the Kalman filtering algorithm is used for signal processing,which can effectively reduce signal fluctuations and measurement errors,and improve measurement accuracy.And then the sensor directionality reference matrix for each sensor is established,and the MUSIC algorithm is used for data matching of arbitrary incoming signal to obtain accurate AOA.After experimental verification,the proposed algorithm can reduce the localization error to less than 5 degrees,which effectively improves the measurement accuracy.

关 键 词：局部放电 方向性 卡尔曼滤波 MUSIC 

分 类 号：TM835[电气工程—高电压与绝缘技术]