A Fault Feature Extraction Model in Synchronous Generator under Stator Inter-Turn Short Circuit Based on ACMD and DEO3S

This paper proposed a new diagnosis model for the stator inter-turn short circuit fault in synchronous generators.Different from the past methods focused on the current or voltage signals to diagnose the electrical fault,the sta-tor vibration signal analysis based on ACMD(adaptive chirp mode decomposition)and DEO3S(demodulation energy operator of symmetrical differencing)was adopted to extract the fault feature.Firstly,FT(Fourier trans-form)is applied to the vibration signal to obtain the instantaneous frequency,and PE(permutation entropy)is calculated to select the proper weighting coefficients.Then,the signal is decomposed by ACMD,with the instan-taneous frequency and weighting coefficient acquired in the former step to obtain the optimal mode.Finally,DEO3S is operated to get the envelope spectrum which is able to strengthen the characteristic frequencies of the stator inter-turn short circuit fault.The study on the simulating signal and the real experiment data indicates the effectiveness of the proposed method for the stator inter-turn short circuit fault in synchronous generators.In addition,the comparison with other methods shows the superiority of the proposed model.

A fault warning for inter-turn short circuit of excitation winding of synchronous generator based on GRU-CNN

Synchronous generators are important components of power systems and are necessary to maintain its normal and stable operation.To perform the fault diagnosis of mild inter-turn short circuit in the excitation winding of a synchronous generator,a gate recurrent unit-convolutional neural network(GRU-CNN)model whose structural parameters were determined by improved particle swarm optimization(IPSO)is proposed.The outputs of the model are the excitation current and reactive power.The total offset distance,which is the fusion of the offset distance of the excitation current and offset distance of the reactive power,was selected as the fault judgment criterion.The fusion weights of the excitation current and reactive power were determined using the anti-entropy weighting method.The fault-warning threshold and fault-warning ratio were set according to the normal total offset distance,and the fault warning time was set according to the actual situation.The fault-warning time and fault-warning ratio were used to avoid misdiagnosis.The proposed method was verified experimentally.

The Detection of Inter-Turn Short Circuits in the Stator Windings of Sensorless Operating Induction Motors

This work proposes an alternative strategy to the use of a speed sensor in the implementation of active and reactive power based model reference adaptive system (PQ-MRAS) estimator in order to calculate the rotor and stator resistances of an induction motor (IM) and the use of these parameters for the detection of inter-turn short circuits (ITSC) faults in the stator of this motor. The rotor and stator resistance estimation part of the IM is performed by the PQ-MRAS method in which the rotor angular velocity is reconstructed from the interconnected high gain observer (IHGO). The ITSC fault detection part is done by the derivation of stator resistance estimated by the PQ-MRAS estimator. In addition to the speed sensorless detection of ITSC faults of the IM, an approach to determine the number of shorted turns based on the difference between the phase current of the healthy and faulty machine is proposed. Simulation results obtained from the MATLAB/Simulink platform have shown that the PQ-MRAS estimator using an interconnected high-gain observer gives very similar results to those using the speed sensor. The estimation errors in the cases of speed variation and load torque are almost identical. Variations in stator and rotor resistances influence the performance of the observer and lead to poor estimation of the rotor resistance. The results of ITSC fault detection using IHGO are very similar to the results in the literature using the same diagnostic approach with a speed sensor.

Analysis of electromagnetic characteristics of typical faults in permanent magnet wind generators

Due to the harsh actual operating environment of the permanent magnet wind turbine,it is easy to break down and difficult to monitor.Therefore,the electromagnetic characteristics identification of major fault types of large-scale permanent magnet wind turbines is studied in this paper.The typical faults of rotor eccentricity,stator winding short circuit and permanent magnet demagnetization of permanent magnet wind turbines are analyzed theoretically.The wavelet analysis algorithm is used to decompose and reconstruct the abnormal electromagnetic signal waveform band,and the characteristic frequency of the electromagnetic signal is obtained when the fault occurs.In order to verify the effectiveness of the proposed method,a 3.680MW permanent magnet wind turbine was taken as the research object.Its physical simulation model was established,and an external circuit was built to carry out field co-simulation.The results show that the motor fault type can be determined by detecting the change rule of fault characteristic frequency in the spectrum diagram,and the electromagnetic characteristic analysis can be applied to the early monitoring of the permanent magnet wind turbine fault.

Short-circuit Current Characteristics of Wind Generators

To study the effects of wind generators on distribution system protection,the short-circuit current(SCC) characteristics of wind generators is important.Although there are many researches on the issue,a clear agreement has not been reached so far.The SCC characteristics for different wind generators are studied.PSCAD simulation is performed in the same system integrated with different kinds of wind generators,and their results are compared with those reported in IEEE papers.The detection possibility by overcurrent relay(OCR)is discussed based on the simulation results.

Feature extraction of induction motor stator fault based on particle swarm optimization and wavelet packet

To effectively extract the interturn short circuit fault features of induction motor from stator current signal, a novel feature extraction method based on the bare-bones particle swarm optimization （BBPSO） algorithm and wavelet packet was proposed. First, according to the maximum inner product between the current signal and the cosine basis functions, this method could precisely estimate the waveform parameters of the fundamental component using the powerful global search capability of the BBPSO, which can eliminate the fundamental component and not affect other harmonic components. Then, the harmonic components of residual current signal were decomposed to a series of frequency bands by wavelet packet to extract the interturn circuit fault features of the induction motor. Finally, the results of simulation and laboratory tests demonstrated the effectiveness of the proposed method.

基于FFT-LSTM的抽水蓄能发电机定子匝间短路故障诊断方法

定子短路故障是抽水蓄能发电机常见的故障之一,其会对发电机的性能和安全性产生严重影响,为确保抽水蓄能发电机安全稳定运行,提出基于FFT-LSTM的抽水蓄能发电机定子短路故障诊断方法。建立抽水蓄能发电机定子绕组匝间短路故障模型,分析定子绕组匝间短路故障时,发电机定子电、磁相关状态。以抽水蓄能发电机定子绕组匝间短路故障时的三相电流信号为依据,基于磁势相等原理将三相电流变换成两相电流后,利用FFT转换定子两相电流的时域信号为频域信号,获取故障电流频谱图输入LSTM网络中进行处理,输出抽水蓄能发电机定子绕组匝间短路故障诊断结果。实验结果表明,该方法可以更好地区分抽水蓄能发电机正常与故障状态,实现抽水蓄能发电机定子绕组匝间短路故障诊断,且故障诊断的交叉熵损失低。

不对称短路故障下永磁直驱风电机组并网控制策略研究

电网侧发生不对称故障时,永磁直驱风电机组并网电流会发生三相不平衡的问题。针对这一问题,提出一种基于自适应陷波器的网侧换流器控制策略。该控制策略基于解决机组并网电流二倍频分量的思想,在电网侧发生不对称短路故障时,将进入逆变器的dq坐标系下的二倍频电压分量去除,从而使得网侧换流器输出的电流达到三相平衡。本文首先分析了电网侧发生不对称短路故障后永磁直驱风力发电机组的动态响应;然后建立了机侧和网侧换流器的模型,并分别采用了双闭环矢量控制技术和基于自适应陷波器的控制策略;最后进行仿真分析,验证了改进后的控制策略相较于传统控制策略,有效解决了不对称短路故障下并网电流三相不平衡问题。

基于开口变压器法的交流电机定子非激励相绕组匝间短路检测研究

为了解决交流电机定子绕组中线圈绝缘损伤引起匝间短路故障无法准确、快速定位的问题,提出将检测转子绕组匝间短路的开口变压器法移植到检测交流电机定子绕组匝间短路,定子单相添加激励源,非激励相绕组设置故障点,开口变压器检测故障点所在槽,分析故障前后开口变压器绕组感应电动势的变化。首先阐述开口变压器检测定子非激励相的工作原理,分析正常和故障状态下通过开口变压器铁心漏磁通的表达式,进一步得到开口变压器绕组感应电动势表达式,获取故障变化规律。随后建立交流电机电磁仿真模型,进行仿真分析,最后用一台定子样机进行实验验证。结果表明:故障状态下,随着故障程度的加深,故障点所在槽的开口变压器感应电动势随之减小,证明了开口变压器可以作为离线检测交流电机定子非激励相绕组匝间短路故障的有效手段。

基于Hotelling T2-BiLSTM的同步调相机故障诊断方法

同步调相机故障会严重影响特高压直流输电工程的稳定性。针对特高压电网中不对称电压条件下同步调相机励磁绕组匝间短路故障难以识别问题,提出基于霍特林T2-双向长短期记忆网络(Hotelling T2-BiLSTM)的同步调相机故障诊断方法。首先,从三相电压、三相电流、励磁电流、转子振动和无功功率中提取故障特征,计算Hotelling T2统计量以构建故障检测指标;然后,采用BiLSTM模型对特征进行分类,并利用逻辑回归层进行故障诊断;最后,在动模实验室中进行实验验证其有效性。实验结果表明,所提方法具有较高的故障诊断精度。

基于d-q变换及WOA-LSTM的异步电机定子匝间短路故障诊断方法

为了实现对异步电机定子绕组匝间短路故障的可靠在线诊断,提出一种基于d-q变换及鲸鱼优化算法(WOA)优化的长短期记忆网络(LSTM)的故障诊断方法。通过理论推导可知,d-q变换可有效提取定子电流中的特征频谱数据。采用鲸鱼优化算法对长短期记忆网络中的3个关键参数进行优化,建立WOA-LSTM故障分类模型。为了验证基于d-q变换和WOA-LSTM故障诊断方法的有效性,分别以小波变换、快速傅里叶变换及d-q变换提取电流频谱数据作为输入数据集,以一台YE2-100L1-4型异步电机为实验对象进行实验验证。研究结果表明:相比于小波变换及快速傅里叶变换,采用d-q变换能更准确的提取出定子电流中的故障特征,更精确地反映电机故障状态,有助于提高故障分类准确率;相比于传统的LSTM算法,经WOA优化后的LSTM算法分类准确率可达98.3%,能可靠地实现不同程度匝间短路故障的诊断。

Simplified mathematical model of inter-turn short circuit of field windings in hydro-generators and its application

Inter-turn short circuit of field windings is a common electrical fault of generators.Simulation is an important method of investigating the fault and providing data support for fault monitoring.However,huge numbers of pole pairs and damper loops in large hydro-generators would lead to lengthy calculation time,hindering scientific research and engineering application.To deal with this problem,we analyze a theoretical basis for a damper winding simplified model and then propose an equivalent treatment method.Through the analysis of steady-state current harmonic characteristics of generators with different stator winding configurations during the fault,the simplified models suitable for steady-state calculation are derived from two aspects,namely,additional rotor harmonic current frequency characteristics and the relationship of the amplitude as well as the phase of each branch current of the stator.The calculation and experimental results of the two simplified models are then compared to verify the models' correctness.A calculation example of the Three Gorges left bank VGS generator shows few deviations between the calculation results of the simplified model and the original model.Moreover,the calculation time using the simplified model is 1/1500 that using the original model,which provides a more effective tool for on-line fault monitoring.Finally,the sensitivity-verification application of the fault-monitoring scheme based on the stator steady-state unbalanced current RMS is depicted.The result shows that the scheme can monitor two-turn short circuits of field windings in the Three Gorges generator and provide high sensitivity.

基于二维CNN与多源机电信息融合的同步电机转子匝间短路故障诊断方法

为提高同步电机转子绕组匝间短路故障的诊断准确率,以一台型号为SDF-9的一对极同步发电机为研究对象,提出了一种基于二维卷积神经网络(Convolutional Neural Networks, CNN)与多源机电信息融合的匝间短路故障诊断方法。首先选取故障前后的定子环流、转子振动、定子振动信号为故障特征,采用信号-图像转换方法将一维时序信号转化为二维灰度图像。其次将处理后的图像分别作为二维CNN模型的前置输入进行训练。最后采用D-S证据理论将3种证据体的输出概率进行决策融合。结果表明:该方法消除了单一信号易受传感器故障及环境变化的影响,故障诊断准确率显著提高,并与其他传统故障诊断算法的诊断结果进行对比分析,验证了此方法的有效性。

基于光纤漏磁场测量的变压器磁平衡保护研究

针对变压器绕组变形、轻微匝间故障等早期故障,传统的保护方案一般难以进行有效的诊断,根据变压器绕组漏磁场变化可以灵敏地检测出绕组的早期故障,但缺乏适用于工程应用的绕组漏磁场分析的解析方法和在线测量方案。针对这些问题,该文计算了简化模型下的变压器绕组漏磁场分布,通过测量绕组上、下表面和中部的漏磁感应强度,提出故障分量磁平衡保护的整定方法和判别逻辑。最后,建立了Ansys的仿真模型和动模实验模型,验证了保护方案具有不受负荷变化及不受励磁涌流的影响,并且区内故障检测灵敏度高的优点。

基于阶跃激励响应的牵引电机定子早期匝间短路故障诊断方法

为了实现对牵引电机定子绕组匝间短路早期故障的可靠诊断,文章提出了一种基于阶跃激励稳态响应电流的故障诊断方法。首先根据牵引电机三相定子绕组匝间短路模型,对定子绕组任意两相施加阶跃激励,推导出3种情况下的响应电流表达式,并依据响应电流稳态值的变化特征提出新的故障特征分量;然后,搭建故障电机仿真模型,分析短路电阻和短路故障严重程度对响应电流的影响,研究故障特征分量对早期匝间短路故障诊断的有效性与可靠性;最后搭建试验平台,分析当电机固有不对称时,匝间短路故障对故障特征分量的影响。仿真与试验结果表明,该故障特征分量可以表示早期的匝间短路故障及其严重程度,并且能滤除电机固有不对称的影响。基于阶跃激励稳态响应电流的诊断方法操作便捷,结果可靠性高,对保护牵引系统的安全具有极大意义,且具备极大的工程应用价值。

西北电网330 kV尖樊线人工短路试验中接地距离保护适应性分析

以风电为代表的新能源场站的故障特征对传统距离保护的附加阻抗产生了新的影响,导致保护性能降低。而现有距离保护适应性研究缺乏对单相接地故障场景的分析。为此,结合西北电网于尖樊线进行的2次人工短路试验数据,基于多种控制策略下的风电场故障特征,分析单相接地故障下接地距离保护附加阻抗系数,进而判断保护适应性。研究发现网侧保护附加阻抗系数较小,两侧电源故障电流对保护影响较小;而风电场侧保护附加阻抗系数较大,两侧电源故障电流对保护影响较大,导致保护拒动。

新型同步调相机转子匝间短路故障定位方法

转子绕组匝间短路故障是新型同步调相机的一种典型故障,对调相机长期运行和电网稳定都有严重影响。为保障新型同步调相机高可靠稳定运行,文中提出一种转子绕组匝间短路故障在线诊断与定位的方法。从故障导致的气隙磁场磁动势畸变出发,推导出定子同相两支路将出现偶次谐波环流现象,并通过对支路环流进行傅里叶分解,提取谐波中的明显特征量。对该特征量进行分析,得出其大小仅与故障所在转子上的空间位置有关,而与故障匝数无关的结论,最后通过查表的方式来实现故障诊断与定位。文中基于已规模投入使用的TTS-300-2型同步调相机开发有限元软件的仿真模型,并搭建基于新型调相机的模拟机实验平台进行实验。仿真与实验结果验证了利用支路环流谐波进行转子匝间短路故障定位的有效性。

基于对称分量法的调相机定子故障特征分析

传统同步调相机定子绕组匝间短路故障机理分析方法通常认为电机定子电流接近三相对称,并以此为基础建立同步调相机故障电流的数学表征。但是,一旦发生定子绕组匝间短路故障,同步调相机三相定子电流的对称性将遭到破坏,使得传统故障机理分析方法所建立的数学表征无法准确反映电机内部电气量的变化。文中通过引入对称分量法,建立故障后同步调相机瞬时有功/无功功率的数学模型,提出利用瞬时有功/无功功率中的2次谐波进行定子绕组匝间短路故障诊断。仿真和实验的结果表明:相较于利用定子电流3次谐波与基波幅值之比诊断故障的传统方法,文中方法在轻微故障状态下能提高至少7倍的诊断灵敏度,更易完成早期故障诊断。同时,所提方法中的故障特征量不受同步调相机工况和故障位置的影响,具有强鲁棒性。

基于d-q理论的双馈异步电机定子匝间短路故障诊断方法

为实现双馈异步电机定子绕组匝间短路的早期故障诊断,提出一种基于转子电流特征频率分量的故障诊断方法 .首先,通过分析故障后电机的电磁特性,得到故障后转子电流中会产生特征频率分量的结论 .然后,通过对转子单相电流进行特殊的相移构造出三相电流,并对该组电流进行d-q变换,利用理论推导证明d-q变换后的直流分量幅值能够反映特征谐波的大小,将直流分量作为故障特征量进行双馈异步电机匝间短路故障的诊断.最后,依据有限元法建立故障前后电机的仿真模型,对不同工况下故障特征量的变化进行研究.结果表明:基于d-q理论提取的故障特征量与定子绕组的短路匝数呈正相关,且在转速变化和电压不平衡时也可有效诊断出匝间短路故障;通过设置合理的故障阈值可实现对双馈异步电机定子绕组匝间短路故障的精确辨识.研究结果可以为电机绕组匝间短路故障诊断提供参考.

风光电源故障暂态解析及实用化短路电流峰值计算

研究风光电源的故障暂态过程及短路电流峰值能为设备选型及保护整定提供重要依据。然而,现有的风光电源暂态短路电流计算模型过于依赖参数,计算模型难以满足工程应用需求。因此,该文首先分别对光伏电源、永磁同步风机及双馈感应风机进行故障暂态解析,继而构建形式简洁实用的短路电流峰值表达式。对于光伏电源及永磁同步风机,在恒功率控制阶段建立了基于故障期间电源出力变化的暂态短路电流计算模型;在限幅控制阶段通过分析阻尼比系数,得到短路电流峰值的实用化表达式。对于双馈感应风机,通过分析其故障后定转子磁链的耦合关系,得到Crowbar电阻投入阶段短路电流的简化条件,进而求解出短路电流峰值表达式。最后通过录波数据与仿真数据验证了理论的可行性和正确性。