Parameter identification algorithm for fault location using one terminal data based on frequency domain

This paper presents a novel algorithm of fault location for transmission line.Solving the network spectrum equations for different frequencies the fault can be located accurately by this algorithm with one terminal data of voltage and current,and the identified parameters,such as fault distance, fault resistance,and opposite terminal system resistance and inductance.The algorithm eliminates the influence of the opposite system impedance on the fault location accuracy,which causes the main error in traditional fault location methods using one terminal data.A method of calculating spectrum from sampled data is also proposed.EMTP simulations show the validity and higher accuracy of the fault location algorithm compared to the existing ones based on one terminal data.

Fault Diagnosis for a Diesel Valve Train Based on Time-Freq uency Analysis and Probabilistic Neural Networks

The cone-shaped kernel distributions of vibration acceleration signals, whichwere acquired from the cylinder head in eight different states of a valve train, were calculatedand displayed in grey images. Probabilistic Neural Networks ( PAW) was used to classify the imagesdirectly after the images were normalized. By this way, the problem of fault diagnosis for a valvetrain was transferred to the classification of time-frequency images. As there is no need to extractfeatures from time-frequency images before classification, the fault diagnosis process is highlysimplified. The experimental results show that the vibration signals can be classified accurately bythe proposed methods.

Improved Leap-frog Method for Time-domain Fault Location

The partial differential equation(PDE)solution of the telegrapher is a promising fault location method among time-domain and model-based techniques.Recent research works have shown that the leap-frog process is superior to other explicit methods for the PDE solution.However,its implementation is challenged by determining the initial conditions in time and the boundary conditions in space.This letter proposes two implicit solution methods for determining the initial conditions and an analytical way to obtain the boundary conditions founded on the signal decomposition.The results show that the proposal gives fault location accuracy superior to the existing leap-frog scheme,particularly in the presence of harmonics.

利用振动幅值进行滚动轴承外滚道故障定位

滚动轴承在机械传动中占有十分重要的地位,其运行状况直接影响着机械的运行效率。因此,对滚动轴承故障的研究具有十分重要的理论意义和现实意义。该文章在故障诊断的基础上提出一种故障定位的新方法。该方法利用三个振动传感器采集滚动轴承运行过程中的振动信号,然后利用相关分析法与EMD算法对其进行去干扰处理,提取振动信号的幅值,并计算其衰减量。利用三个传感器采集到的三处振动信号衰减量来分析计算故障的准确位置。该方法简单,提取特征值少,定位精度高。且该方法不仅能准确定位滚动轴承外滚道单点故障,而且可同时定位出多个故障点。这在以往的定位方法中是很难实现的。

A fast time-frequency response based differential spectral energy protection of AC microgrids including fault location

This paper proposes a pattern recognition based differential spectral energy protection scheme for ac microgrids using a Fourier kernel based fast sparse time-frequency representation(SST or simply the sparse S-Transform).The average and differential current components are passed through a change detection filter,which senses the instant of fault inception and registers a change detection point(CDP).Subsequently,if CDP is registered for one or more phases,then half cycle data samples of the average and differential currents on either side of the CDP are passed through the proposed SST technique,which generates their respective spectral energies and a simple comparison between them detects the occurrence and type of the fault.The SST technique is also used to provide voltage and current phasors and the frequency during faults which is further utilized to estimate the fault location.The proposed technique as compared to conventional differential current protection scheme is quicker in fault detection and classification,which is least effected from bias setting,has a faster relay trip response(less than one cycle from fault incipient)and a better accuracy in fault location.The significance and accuracy of the proposed scheme have been verified extensively for faults in a standard microgrid system,subjected to a large number of operating conditions and the outputs vindicate it to be a potential candidate for real time applications.

基于主动探测原理的直流配电线路短路故障测距

为克服对端系统助增作用的影响,实现直流配电线路短路故障的准确测距,提出一种主动探测式的故障测距原理。故障发生后,设计限流策略限制短路电流,进而切换至主动探测控制策略下,向直流线路注入特征频率探测信号。根据特征频率下故障等效电路的激励与响应特性,构建故障测距方程,实现了基于故障分析法的单端量故障测距。基于PSCAD电磁暂态仿真软件搭建了对应模型,仿真验证了不同故障位置和故障过渡电阻情况下测距原理的性能,采用特征频率探测信号构建测距方程,克服了对端电源助增作用的影响,测距结果的相对误差在0.5%以内。

基于参数优化VMD和TET的柔直线路单端故障测距方法

单端行波故障测距方法在考虑频变波速影响时需要提取故障行波时频域特征,但现有方法存在时频分辨率较低、波头识别困难和波速计算不准确的问题。为此,提出一种基于参数优化变分模态分解(variational mode decomposition,VMD)和瞬态提取变换(transient extraction transform,TET)的单端故障定位方法。首先,利用麻雀搜索算法(sparrow search algorithm,SSA)优化VMD参数,提取含有故障特征的高频模态分量。然后,对该模态分量进行瞬态提取变换,通过去除短时傅里叶变换中模糊的时频能量,保留与信号瞬态特征密切相关的时频信息,得到故障行波时频域全波形。最后,在故障行波全波形中提取主频分量并标定初始波头与第二反射波头,通过计算主频分量下的波速度,结合行波定位方法实现单端故障测距。在PSCAD/EMTDC中搭建四端柔性直流电网的仿真结果表明,所提算法对过渡电阻和噪声具有较强的耐受性,即使在较低采样率下也能实现准确的故障定位。

基于台区剩余电流监测的接线错误用户漏电故障定位

台区漏电故障定位是供电企业运维中的痼疾。低压用户零线、地线接线错误是工程上的常见故障,可导致台区剩余电流超标,如不能准确定位将无法投入台区三级剩余电流保护,将严重威胁用户人身安全。既有漏电故障研究多围绕绝缘故障的电弧频谱特征展开,较少考虑接线错误因素影响。该文围绕农村TT接线台区的用户接线错误所致漏电故障,分析台区剩余电流在正常运行和用户接线错误条件下的波动特性。利用接线错误用户负荷电流主导台区剩余电流波动的特点,提出根据台区剩余电流和用户负荷电流进行回归分析定位接线错误用户的方法,将对台区剩余电流显著性影响程度高的用户识别为零线、地线接线错误用户。基于实验测试数据进行的仿真分析验证了所提方法的有效性。

基于小波分析的输电线路单端故障定位方法

为精准判别输电线路单端故障的位置,提出基于小波分析的输电线路单端故障定位方法。联合零序电压与故障绕组系数,求解输电转矩指标的取值范围,完成对单端故障暂态特征量的计算。分别从连续小波变换、离散小波变换两方面来完善小波分析理论,获取故障暂态特征量指标的实际取值范围,并以此为基础,确定暂态定位参数的具体取值结果,实现对输电线路单端故障行为的全局定位。实验结果表明,小波分析理论作用下,单端故障节点处最大电压检测差值为5 V、最大电流检测差值为0.1 A,误差较小,符合精准判别输电线路故障的应用需求。

Fault Location and Classification for Distribution Systems Based on Deep Graph Learning Methods

Accurate and timely fault diagnosis is of great significance for the safe operation and power supply reliability of distribution systems.However,traditional intelligent methods limit the use of the physical structures and data information of power networks.To this end,this study proposes a fault diagnostic model for distribution systems based on deep graph learning.This model considers the physical structure of the power network as a significant constraint during model training,which endows the model with stronger information perception to resist abnormal data input and unknown application conditions.In addition,a special spatiotemporal convolutional block is utilized to enhance the waveform feature extraction ability.This enables the proposed fault diagnostic model to be more effective in dealing with both fault waveform changes and the spatial effects of faults.In addition,a multi-task learning framework is constructed for fault location and fault type analysis,which improves the performance and generalization ability of the model.The IEEE 33-bus and IEEE 37-bus test systems are modeled to verify the effectiveness of the proposed fault diagnostic model.Finally,different fault conditions,topological changes,and interference factors are considered to evaluate the anti-interference and generalization performance of the proposed model.Experimental results demonstrate that the proposed model outperforms other state-of-the-art methods.

基于小波分析的电网电压行波故障定位系统

电网电压行波故障定位系统的电压行波波头辨识错误率较高,故障定位距离结果与实际距离结果不一致,因此,提出基于小波分析的电网电压行波故障定位系统设计研究。设计一种传感电路获取电压行波信号,引入小波分析算法去除电压行波信号中的噪声,有效融合LSTM算法与ADF检验方法制定电压行波波头辨识方法,确定电压行波波头到达时刻,计算电网故障距离,实现电网电压行波故障定位。实验数据显示,设计系统获得的电压行波波头辨识错误率最小值为1%,该系统定位距离结果与实际结果一致,证实了其具备较佳的应用效果。

基于领域分析的结构线性静力软件串并行一致化方法

并行CAE软件的计算结果串并行一致性是其计算结果可信的必要条件。然而,软件研发时常引入串并行不一致缺陷,其形式众多,现象相互耦合,散布于海量代码中,成为实现CAE软件串并行一致性的挑战。文中以结构线性静力软件的串并行一致性需求为切入点,针对现有的“专家知识法”与“缺陷定位法”应用于CAE软件串并行一致化时存在的粒度粗、准度差、成本高和缺乏系统性问题,引入领域分析方法,并与专家知识和数据流状态比对结合,提出了一种适用于结构线性静力的串并行一致化方法,实现了结构线性静力软件串并行不一致缺陷的细粒度、高准度与低成本系统性识别与修复。基于前述方法形成相关工具,并将方法与工具应用于SSTA的串并行一致化,识别并修复其中8处串并行不一致缺陷,使其通过90余真实模型的串并行一致考核,并实现串并行结果严格一致;同时,该方法与工具还将串并行不一致缺陷定位耗时由平均大于两人天降低至数人时。

基于双数据源的直流输电线路故障测距方法

介绍了针对直流输电线路的双端行波法、单端行波法和时域故障分析法等故障测距方法的原理、特点及应用现状。针对实际工程应用中出现的行波测距法数据来源可靠性相对较低以及时域故障分析法故障测距精度低等问题,提出了时域故障分析法与行波法相结合的直流输电线路综合故障测距方法。利用双数据源,包括高速数据及低速数据,通过单端行波法/时域法分别计算可能故障点,并利用小波变换模极大值的幅值、极性特征筛选确定故障点,将单端行波测距法的精度优势和时域法测距数据的可靠性优势相结合。最后通过PSCAD仿真对该方法的有效性进行了验证。

电力系统故障分析与保护策略优化

文章旨在深入研究电力系统故障分析的方法及其保护策略的优化。随着能源结构的转型和智能电网的发展,电力系统的稳定运行显得尤为重要。文章介绍了电力系统常见的故障类型、产生原因及其对系统的影响,以及电力系统故障分析的基本原理和方法,包括故障录波、数据分析和故障定位等关键技术。在此基础上,文章综述了传统保护策略的应用和局限,并探讨了智能电网背景下保护策略的发展趋势。

模块化多电平换流器子模块故障分析与诊断方法综述

随着模块化多电平换流器(Modular Multilevel Converter,MMC)的广泛应用,其内部存在的问题也日益突出并成为制约系统稳定运行的主要因素。MMC子模块拓扑结构分为半H桥型、全H桥型和双箝位型3种,其中最典型的是半H桥型子模块,其内部由2个IGBT以及与其反并联的二极管和1个电容组成。在运行平稳的电路中,若子模块内部二极管、IGBT、储能电容任一发生故障,都可能会引起系统内部电路结构的变化,致使系统无法稳定运行,甚至直接崩溃。因此,对子模块内部故障的研究很有意义。针对IGBT、二极管和电容在子模块中的故障情况以及故障诊断与定位的方法进行了详细的介绍与分析。

基于大数据分析的变电站电力通信网络故障定位方法

变电站电力通信网络是电力系统安全稳定运行的关键基础设施。随着网络规模扩大和复杂度增加,传统故障定位方法已难以满足快速精准定位的需求。文章提出一种基于大数据分析的故障定位方法,通过智能分析海量运行数据,自动提取故障特征,构建故障定位模型。实验结果表明,该方法显著提高了故障定位准确率和效率,为变电站电力通信网络的智能化运维提供了新的解决方案。

基于图卷积神经网络的配电网故障定位方法及算例分析

阐述为建立配电网故障的自动化定位方法,构建故障定位的算法模型。借助该算法从配电网的拓扑网络结构中提取节点特征和拓扑特征,将其作为模型输入,再经过数据标准化处理、图卷积层运算、全连接层运算,实现故障区段定位。检验结果显示,经过80次迭代后,此算法模型的定位精确度可以达到96%。

Application of local wave ti me-frequency method in reciprocating mechanical fault diagnosis

To diagnosethe reciprocating mechanical fault.We utilizedlocal waveti me-frequency approach.Firstly,we gave the principle.Secondly,the application of local wave ti me-frequency was given.Finally,we discusseditsvirtue in reciprocating mechanical fault diagnosis.

暂态特征模量时频分析的电缆型配电网单相接地故障区段定位

配电电缆导体与屏蔽层耦合复杂,电缆发生单相接地故障后,在复杂条件下(如高阻故障、电弧等)故障稳态特征不显著、暂态特征多变,复杂网络中准确定位故障电缆困难。针对典型配电网电缆结构参数特征,首先论证故障暂态信号解耦的可行性,提出相模变换矩阵的一般计算方法;然后,根据电缆发生不同类型单相接地故障前、后暂态模量状态,筛选出能够有效反映单相接地故障的特征模量;最后,考虑配电网拓扑和测量点布置,分析故障后电缆分支节点处的暂态电流特征模量频率分量的幅值分布和极性因子,构建基于空间–测量矩阵的单相接地故障区段定位判据。利用PSCAD/EMTDC搭建10kV电缆型配电网故障仿真模型,典型案例计算结果表明:所提方法能够实现不同条件下单相接地故障区段的定位,与已有方法相比具有优势。

基于特勒根拟功率定理的直流输电线路故障测距

高压直流输电系统的网络结构和故障特性对线路故障测距方案准确度提出更高要求,对此,该文提出一种基于特勒根拟功率定理的直流输电线路故障测距方案。首先,在分析直流线路贝瑞隆模型的基础上,首次提出特勒根拟功率定理应用于直流线路故障分析的方案,并给出拟功率解析表达式。其次利用贝瑞隆模型构建拟功率基准值,并根据故障点处基准值与计算值相等的原则实现故障测距。最后,通过大量仿真,验证理论推导的正确性以及拟功率能有效反应故障位置,并验证该方案不受过渡电阻及故障类型的影响。该研究实现了低采样频率下高精度测距的目标。