基于振动云图HOG和SVM的变压器绕组松动故障诊断方法  

Diagnostic Method for Transformer Winding Looseness Based on HOG of Vibration Cloud Picture and SVM

作　　者：朱梓倩 刘蓉[1] 付瑜 李继胜[1] 杨怡晴 ZHU Ziqian;LIU Rong;FU Yu;LI Jisheng;YANG Yiqing(School of Physic&Information Technology,Shaanxi Normal University,Xi’an 710119,China;Xinghua College,Chang’an University,Xi’an 710000,China)

机构地区：[1]陕西师范大学物理与信息技术学院,西安710119 [2]长安大学兴华学院,西安710000

出　　处：《高压电器》2019年第11期227-231,238,共6页High Voltage Apparatus

基　　金：陕西省自然科学基金(2015GY130,2018GY016);中央高校基金(GK201603023)~~

摘　　要：电力变压器是实现电压变换和电能分配的重要电力设备。针对变压器机械故障,振动分析法具备很强的科学性和可行性。文中搭建了基于振动传感阵列的变压器振动测试系统,研究了单相变压器油箱表面振动分布,分别测量绕组在正常状态和故障状态下的油箱振动云图,提取振动云图的方向梯度直方图(HOG)特征,选择支持向量机(SVM)为学习训练方法,形成二类分类器,分辨变压器绕组的正常状态与故障状态。最终提出基于振动云图HOG和SVM的变压器绕组松动故障诊断方法,实验验证该方法有很高的识别率。Power transformer is an important equipment of power system. For transformer mechanical fault,vibration analysis method has scientific and strong feasibility.In this paper,a transformer vibration measurement system based on vibration sensor array is built.The vibration distribution of single-phase transformer tank surface is studied.The vibration cloud pictures of the oil tank under normal and fault conditions are measured respectively.Histograms of oriented gradient(HOG) of the vibration cloud pictures are extracted and the support vector machine(SVM)is selected as the learning method. Two types of classifiers are formed to distinguish normal and fault states of transformer winding. Finally,a fault diagnosis method of transformer winding loosening based on vibration image HOG and SVM is proposed.The experimental results show that the method has a high recognition rate.

关 键 词：变压器绕组 振动云图 HOG特征 支持向量机 

分 类 号：TM4[电气工程—电器]