基于振动频响法的变压器绕组松动故障检测方法研究北大核心CSCD

变压器是电力系统的重要设备,在长期运行中会出现绕组松动、变形等故障,影响电力系统的正常工作,因此对变压器绕组健康状态进行评估极为重要。提出利用振动频响法获取变压器绕组的振动频响函数,对比绕组故障状态与健康状态下的振动频响函数,将两者之间的相关系数作为判断变压器绕组故障与否的依据。随后,对比健康状态与4种不同程度松动状态下变压器绕组的振动频响函数,探讨利用相关系数判断变压器绕组松动故障程度的可行性。本研究结果对判断变压器绕组运行故障具有一定的指导意义。     

用频响法测量变压器绕组变形

目前,供电系统中变压器事故的50％以上是变压器出口短路引起的．这就需要掌握事故后变压器绕组的变形状况。以及具体的变形方式,变形的严重程度。这对于判断故障后的变压器能否迅速投入运行具有重要的参考价值。     

变压器绕组松动机械特性研究

为研究基于振动特性的变压器故障检测方法,本文从变压器绕组的机械稳定性研究出发,通过建立变压器绕组机械动力学特性模型,利用ANSYS有限元仿真分别对变压器绕组正常和松动状态进行建模研究,得到了变压器绕组两种状态下的固有振动特性,为进一步研究变压器绕组故障检测方法打下基础。     

频响阻抗法诊断变压器绕组变形

变压器绕组变形是变压器的主要故障类型之一,严重威胁电网安全。为此,提出频响阻抗法诊断变压器绕组变形。研究了变压器绕组在低频和中频段的阻抗频率特性,以频率响应的测试接线为基础,测量相关的电压和电流值,对测得的电气数据进行处理以获得阻抗频率曲线,通过对比曲线间的差异实现对变压器绕组变形的诊断。建立了变压器绕组变形的仿真模型,通过改变模型中不同类型元件的参数值模拟绕组故障。仿真结果表明该方法能明显反应绕组故障,验证了频响阻抗法的有效性。     

基于振动的变压器绕组松动缺陷诊断方法

将理论与实验相结合,对变压器绕组松动缺陷诊断方法进行研究。理论上定义了基于预紧力的变压器绕组松动缺陷特征值,该特征值与变压器绕组预紧力之间存在规律的单调区间,提出利用该关系进行缺陷诊断,该方法不受电流影响,因而适用于负荷波动下的在线监测。在实验中采用应变片桥式电路测量预紧力,施加不同的预紧力进行绕组松动缺陷设置。利用锤击法测算油箱固有频率,考虑预紧力变化对油箱固有频率的影响,以不受共振影响的测点为有效测点。分析不同预紧力大小、不同电流情况下变压器有效测点信号的特征值,确定故障阈值与预警阈值,实现绕组松动缺陷诊断以及缺陷相定位。     

用频响分析法判断变压器绕组变形

提出了变压器绕组变形频响分析法测试中不同接线组别变压器的接线方式,分析了分接开关档位、套管电容量、出口引线长度、线圈饼间电容、不同电压等级线圈之间距离等因素引起变压器频响曲线变化的特征,提出了变压器绕组变形测试结果的分析方法。     

基于振动信号的变压器绕组松动故障诊断方法

提出了基于运行中变压器表面振动信号的绕组松动故障诊断模型和诊断方法。首先,分析了绕组振动幅值与电流、预紧力、铁芯振动、非线性因素的关系,确定振动信号中100 Hz为绕组松动的特征频率,提出分离绕组振动幅值和铁芯振动幅值的方法;提出绕组松动诊断模型和基于该模型的平均安全余量,利用待检测变压器在一组负载电流下的绕组振幅计算平均安全余量,由此定量判断绕组的松动状态。利用有限元仿真和现场实验分别对诊断模型和诊断方法进行检验,实验结果显示平均安全余量在1±0.5之外时存在松动故障,值越远离1,松动程度越大。该方法解决了变压器实际运行中绕组和铁芯振动基频相同、矢量叠加相互影响的问题及实际运行中负载变化,电流不同,仅用某个电流下的振幅判断精度受限的问题,且对松动程度量化表示,易于判断。     

变压器绕组变形频响法分频点研究

运用基于频率响应法(即FRA法)的仪器诊断变压器绕组变形的工作目前已经相当广泛，但是在运用相关系数型学进行诊断时还存在一些不足，例如各地判据不统一，各地自行制定的判据分频不一致等。针对这种情况，结合大量的测试结果分析，找到了较为合理的分频点。     

大型变压器绕组频响试验中常见问题分析

变压器频响试验常见的一些影响试验结果问题,通过对几种典型情况的举例,对频响试验中可能会遇到的一些问题进行了分析比对,可以给读者一定的参考建议,以免类似情况发生。     

频率响应法在变压器绕组变形测试中的应用

电力变压器是电力系统的主要设备之一,进行变压器绕组变形测试对正确判断变压器在受到冲击力后是否产生绕组变形,从而保障变压器的安全运行具有重要意义。本文介绍了应用频率响应法对变压器进行绕组变形测试的原理、方法,对现场开展变压器绕组变形测试、确保电网安全运行具有指导作用。     

Sweep frequency response analysis (SFRA) for the assessment of winding displacements and deformation in power transformers

The sweep frequency response analysis (SFRA) is an analysis technique for detecting winding displacement and deformation (among other mechanical and electrical failures) on power and distribution transformers. Nowadays, there is an increasing interest in SFRA method because of its sensibility in detecting mechanical faults without opening the unit. SFRA as a diagnostic technique must integrate both the off-line measurements and the interpretation of the data in order to provide an assessment of the condition of the windings. However, guidelines for the measurement and record interpretation are not available. The evaluation is presently done by experts in the topic through the visual inspection or with the help of statistical parameters such as the correlation coefficient and the standard deviation. However, criteria like the limits of normal variation of the parameters, and the features observed in the records in the presence of a determined type of fault could not to coincide. Although, there are some proposals for making the interpretation more objective, neither of them integrate human expertise along with the different kind of parameters obtained from the evaluation of the records in a diagnostic model. This paper presents a survey on the alternatives in the measurement techniques and interpretation of SFRA measurements, describing some sources of uncertainty in applying this methodology.     

Improved modelling of power transformer winding using bacterial swarming algorithm and frequency response analysis

The paper discusses an improved modelling of transformer windings based on bacterial swarming algorithm (BSA) and frequency response analysis (FRA). With the purpose to accurately identify transformer windings parameters a model-based identification approach is introduced using a well-known lumped parameter model. It includes search space estimation using analytical calculations, which is used for the subsequent model parameters identification with a novel BSA. The newly introduced BSA, being developed upon a bacterial foraging behavior, is described in detail. Simulations and discussions are presented to explore the potential of the proposed approach using simulated and experimentally measured FRA responses taken from two transformers. The BSA identification results are compared with those using genetic algorithm. It is shown that the proposed BSA delivers satisfactory parameter identification and improved modelling can be used for FRA results interpretation.     

基于振动信号的变压器铁心与绕组故障区分方法

针对变压器铁心、绕组由于机械结构相连,铁心故障与绕组故障区分困难的问题,提出采用基于振动信号的变压器铁心与绕组故障的区分方法,通过对比分析铁磁材料磁致伸缩和绝缘垫块弹性形变的非线性特性差异,结合实验分别获取变压器铁心、绕组振动信号,在频域研究了变压器铁心、绕组振动信号的非线性特性,通过分析不同条件下振动信号高次谐波能量...     

用频率响应法发现一台主变绕组变形实例

介绍了应用绕组变形测试仪准确检测出一台大型变压器发生故障后低压绕组发生严重变形的事例。检出变形后，及时更换了变形的绕组，从而避免了因绕组变形可能造成的另一次突发事故。     

基于格拉姆角场与迁移学习-AlexNet的变压器绕组松动故障诊断方法

绕组松动故障是变压器最主要的机械故障之一,尚缺乏有效的智能化诊断方法。为此提出基于格拉姆角场与迁移学习-AlexNet的变压器绕组松动故障诊断方法。变压器稳态运行时的振动信号存在周期性的特点,导致其构建足量具有时间相关性的图像集十分困难,提出了一种样本构建方法用于生成变压器振动信号的格拉姆角场图像集。将生成的图像集送入AlexNet进行迁移学习,获得微调后的神经网络模型。实验结果表明：利用该样本构建方法生成的图像集作为训练集和验证集,建立的卷积神经网络模型训练准确率与验证准确率均达到99%以上;利用变压器周期性振动信号生成的图像集作为测试集,测试准确率达到99%以上,实现了变压器绕组松动故障的准确诊断,并为周期性信号运用具有时间相关性的图像变换方法构建足量样本集提供了一种新思路。     

频率响应法在诊断绕组变形中的应用

介绍了应用频率响应分析法检测变压器绕组变形的两个实例。指出在检测中通过对前后频谱曲线的分析,能准确有效地发现变压器内部电气及机械事故隐患,对于变压器及电网的安全运行,有着重要意义。但频率响应分析法不一定能够有效反映出变压器绕组变性发生单一扭动变形这类故障,绕组变形的诊断仍需使用多种试验手段综合分析和判断。     

Modelling of winding failures identification using the frequency response analysis (FRA) method

The frequency response analysis method of investigation of windings is one of the methods being introduced more and more, recently. It is being used for the identification of dislocations and deformations of transformer windings as well as for the early detection of winding failures in electrical machines. This method is based on the comparison of the transfer function with reference measurements. The application of this method in the investigation of windings is determined by a measurement of the transfer function and by mathematical modelling. Both methods of determining the transfer function of the windings are being refined and developed. The numerical simulations are aiming at determining the sensitivity of this method and developing the recognition criteria with regard to the type and range of the deformations.     

High frequency model of transformer winding

A high frequency model of transformer winding is used to analyze the voltage oscillations due to various excitations such as the very fast transient overvoltage which occurs at the time of disconnecting switch operations. Usually, a circuit of interlinked inductances and capacitances is used for this purpose, in which circuit parameters have to be properly determined. Previously, those constants have been estimated taking the coil section pair as a unit. In the method proposed here, the section pair can be further subdivided. The time‐domain calculation is conducted combining the frequency analysis and FFT technique. The voltage oscillations of the winding subjected to the lightning impulse are calculated. The correspondence with the experimental results is satisfactory. The response to a chopped impulse shows this method's applicability to high frequency analysis. Since the constants are calculated directly from the design parameters of transformer winding, this technique is particularly useful in developing and designing transformers. © 2003 Wiley Periodicals, Inc. Electr Eng Jpn, 146(3): 8–16, 2004; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/eej.10280     

新型换流变压器绕组振动特性的ANSYS分析

利用ANSYS有限元软件仿真求得新型换流变压器绕组振动模态和绕组振动位移数据。经过Matlab离散数据快速傅里叶变换(FFT)分析波形得到绕组振动频率成分。针对新型换流变压器阀侧绕组、滤波绕组、网侧绕组振动频谱分析,得出绕组振动频率与绕组电流频率存在某种关系的特性。