基于电压阻尼振荡的变压器故障绕组识别方法

doi:10.19595/j.cnki.1000-6753.tces.230314

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摘要

变压器绕组振荡波能够有效反映绕组状态变化,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。本文针对该问题,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4种故障下绕组振荡波数据;然后,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;进而,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(Feature Correlation Degree,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。

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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

Abstract：

The winding fault is a serious transformer fault. The voltage damping oscillation method is an effective method to diagnose the winding health state. However, this method still has the following problems: 1) The voltage damping oscillation of transformer winding continue to fluctuate slightly for a period of time before the end of charging and discharging. In this process, there are lot of irregular maximum points, minimum points and burrs. These invalid extreme points and burrs interfere with the subsequent characteristic processing and analysis of the oscillation wave. 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 is far greater than 5% of the maximum value, which leads to the definition of the effective wave band of the above voltage damping oscillation is no longer applicable. 2) Due to the complexity of on-site testing and external interference, the two voltage damping oscillation signals measured at different time intervals on the same transformer may have small deviations. At present, the time-domain feature extraction of the oscillation wave applied to the transformer is distinguished only by a single curve feature, and the identifiable accuracy is low when diagnosing the fault location and degree. In order to eliminate the interference and obtain more status information of transformer windings , this paper presents a method of transformer winding fault analysis based on the selection of dynamic wave band of voltage damping oscillation: first, build a transformer winding fault simulation platform to obtain the winding oscillation wave data under four kinds of faults: axial displacement, inter disk capacitance, inter pie or inter turn short circuit; Secondly, By analogy with the effectiveness of mechanical system and electrical system, the characteristics of oscillation wave attenuation are analyzed from the perspective of energy conversion, selecting the effective wave band of oscillation wave through defined energy attenuation factor; Then, in the effective band of the oscillating wave test data: obtain the waveform Feature Correlation Degree (FCD) to identify the fault type, At the same time, taking into account the rich feature information between the extreme point and the waveform, construct the oscillating wave binary image based on mathematical morphology to eliminate the measurement interference and extract more stable Tamura texture features to identify the fault location and degree; Finally, based on the distribution rule of characteristic parameter combination, the application analysis is carried out through the actual transformer. The results show that the band interference information dynamically selected is less, the attenuation oscillation regularity is obvious and contains rich feature information. The oscillation wave under four types of faults have certain differences between each other, and exhibit significant variation patterns compared to normal windings. The use of waveform FCD is particularly effective in identifying winding fault types; The oscillation wave under the same fault type exhibit small differences in different fault areas and degrees. Different combinations of four Tamura texture features exhibit good classification performance in identifying fault degrees and types. In general, the waveform FCD and Tamura texture feature based on binarization values extracted under different faults have their obvious separation and clustering. It can realize the recognition and classification of fault type, fault degree and fault region.

Key words： Transformer Voltage damping oscillation Winding fault Dynamic band Waveform feature Texture feature

PACS:

TM614

通讯作者: 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

作者简介: 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

引用本文:

周利军, 员秀程, 王东阳, 周猛, 张俊. 基于电压阻尼振荡的变压器故障绕组识别方法[J]. 电工技术学报, 0, (): 8925-. ZHOU Lijun, YUN Xiucheng, WANG Dongyang, ZHOU Meng, ZHANG Jun. Transformer Fault Winding Identification Method Based on Voltage Damped Oscillation. Transactions of China Electrotechnical Society, 0, (): 8925-.

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