摘要
变压器绕组振荡波能够有效地反映绕组状态变化,实际应用中发现振荡波末期存在不规律振荡行为,影响了基于振荡波的变压器绕组故障诊断准确性。该文针对此问题,首先,搭建变压器绕组故障模拟平台,获取轴向移位、局部翘曲、饼间短路和匝间短路四种故障下绕组振荡波数据;其次,通过定义的能量衰减因子,提出了一种基于电压阻尼振荡的变压器绕组振荡波有效波段动态选取方法;再次,基于确定的有效波段,提出了基于二值化的Tamura纹理特征的特征参数提取方法,并结合波形特征关联度(FCD),提出了用于故障类型(轴向移位、局部翘曲、饼间短路和匝间短路)、区域、程度诊断的特征参数组合并分析了其分布规律;最后,基于特征参数组合的分布规律通过实际变压器进行了应用分析。结果表明,动态选取出的波段干扰信息少、衰减振荡规律性明显且包含丰富的特征信息,可实现对故障类型、故障程度和故障区域的识别分类。
The voltage damping oscillation method is effective for diagnosing winding faults,but it still has the following problems.The voltage-damping oscillation of transformer winding continues to fluctuate slightly for a period before the end of charging and discharging.In this process,there are a lot of irregular maximum points,minimum points,and burrs,which interfere with the subsequent characteristic processing and oscillation wave analysis.According to the existing literature,the oscillation ends when it attenuates to 5%of the maximum value,and all poles in this band are effective extreme points.Through a large number of experiments,it is observed that when the voltage-damping oscillation is no longer attenuated,its stable value often exceeds this threshold.As a result,the definition of the effective wave band of the above voltage-damping oscillation is inapplicable.Due to the complexity of on-site testing and external interference,two voltage-damping oscillation signals measured at different time intervals on the same transformer may have small deviations.However,the time-domain feature extraction of the oscillation wave is distinguished only by a single curve feature,and the identifiable accuracy is low when diagnosing the fault location and degree.Therefore,this paper presents a transformer winding fault analysis method for selecting a dynamic wave band of voltage-damping oscillations.First,a transformer winding fault simulation platform is built,considering four kinds of faults:axial displacement,inter-disk capacitance,inter-pie,and inter-turn short circuits.Secondly,the characteristics of oscillation wave attenuation are analyzed from the perspective of energy conversion,selecting the effective wave band through a defined energy attenuation factor.Then,the waveform feature correlation degree(FCD)is obtained for fault type identification.At the same time,considering the rich feature information between the extreme point and the waveform,the oscillating wave binary image is constructed based on mathematical morphology to eliminate interference and extract more stable Tamura texture features.Finally,according to the distribution rule of characteristic parameter combination,the application analysis is carried out through the actual transformer.The dynamically selected band shows minimal interference,clear attenuation oscillation regularity,and rich feature information.Oscillation waves under four fault types are different from each other,exhibiting significant variation patterns compared to normal windings.The waveform FCD is effective in identifying winding fault types.Oscillation waves exhibit minor differences in fault areas and degrees under the same fault type.Different combinations of four Tamura texture features demonstrate good performance in classifying fault degrees and types.In general,the waveform FCD and Tamura texture feature based on binarization values extracted under different faults have apparent separation and clustering,which can recognize fault type,degree,and region.
作者
周利军
员秀程
王东阳
周猛
张俊
Zhou Lijun;Yun Xiucheng;Wang Dongyang;Zhou Meng;Zhang Jun(College of Electrical Engineering Southwest Jiaotong University,Chengdu 611756 China)
出处
《电工技术学报》
EI
CSCD
北大核心
2024年第10期3218-3231,共14页
Transactions of China Electrotechnical Society
关键词
变压器
振荡波
绕组故障
动态波段
波形特征
纹理特征
Transformer
voltage damping oscillation
winding fault
dynamic band
waveform feature
texture feature
作者简介
通信作者:周利军,男,1978年生,教授,博士生导师,研究方向为电气设备状态检测与故障诊断等。E-mail:ljzhou10@163.com;员秀程,男,1998年生,硕士研究生,研究方向电气设备状态检测及故障诊断。E-mail:13685480501@163.com。
