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.

Fault Diagnosis Based on ANN for Turn-to-Turn Short Circuit of Synchronous Generator Rotor Windings

Rotor winding turn-to-turn short circuit is a common electrical fault in steam turbines. When turn-to-turn short circuit fault happens to rotor winding of the generator, the generator terminal parameters will change. According to these parameters, the conditions of the rotor winding can be reflected. However, it is hard to express the relations between fault information and generator terminal parameters in accurate mathematical formula. The satisfactory results in fault diagnosis can be obtained by the application of neural network. In general, the information about the severity level of the generator faults can be acquired directly when the faulty samples are found in the training samples of neural network. However, the faulty samples are difficult to acquire in practice. In this paper, the relations among active power, reactive power and excitation current are discovered by analyzing the generator mmf with terminal voltage constant. Depending on these relations, a novel diagnosis method of generator rotor winding turn-to-turn short circuit fault is proposed by using ANN method to obtain the fault samples directly, without destructive tests.

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.

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。

双馈异步风力发电机转子匝间短路故障振动特性分析

针对双馈异步风力发电机转子匝间短路的故障振动机理尚不明确且无法为故障诊断提供理论依据的问题,开展了双馈异步风力发电机转子匝间短路故障振动特性分析.首先,结合有限元仿真及解析推导,分析转子匝间短路下双馈异步风力发电机的气隙磁密规律,得到转子所受的不平衡磁拉力;然后,考虑转子不平衡磁拉力的情况下构建双馈异步风力发电机转子-轴承系统非线性动力学模型,利用非线性动力学仿真获取转子匝间短路故障下系统的振动仿真信号;最后,在双馈异步风力发电机故障模拟实验台上进行转子匝间短路故障实验,利用实验分析验证非线性动力学仿真结果的有效性.非线性动力学仿真及实验分析结果均表明,转子匝间短路故障下双馈异步风力发电机转子-轴承系统振动信号的频谱存在转频的谐波成分,通过检测转频的谐波分量可诊断双馈异步风力发电机转子匝间短路故障,有效揭示了双馈异步风力发电机转子匝间短路的故障振动机理.

基于MSET的汽轮发电机转子绕组匝间短路故障诊断

针对汽轮发电机转子绕组匝间短路故障,提出基于多元状态评估技术(MSET)的在线诊断方法。利用滑动窗口和欧氏距离构建状态矩阵,基于MSET构建励磁电流和无功功率计算模型,依据发电机运行状态运行值与计算值的相对偏差均值或残差均值构建匝间绕组短路故障在线诊断方法,并且使用某汽轮发电机运行数据进行验证。结果表明:所构建的在线诊断方法切实可行,满足了转子绕组匝间短路故障诊断应用需要,同时降低了故障误判的可能性。

开口变压器法检测汽轮发电机转子绕组故障的有效性验证

精确、快速检测出汽轮发电机转子绕组短路故障,可以有效缩短故障处理时间、降低停机成本。本文对开口变压器检测转子绕组匝间短路时的感应电压进行了特征分析,指出感应电压在故障前后的相位变化。随后利用有限元软件搭建了一台300MW汽轮发电机的转子模型,设置不同的匝间短路程度和短路位置,获取相对应的开口变压器的感应电压,验证了通过感应电压变化判断转子绕组匝间短路的有效性。

异步电机综合故障实验教学平台设计与开发

由于异步电机实验教学平台多是针对正常工况设计开发的,缺乏对故障状态的模拟和分析,因此造成了教学和实际需求的脱节。该文设计开发的异步电机综合故障实验教学平台可以开展定子绕组匝间故障、转子断条故障、轴承故障实验和在线诊断,该平台综合了异步电机拆解与组装、故障特征分析以及数字信号处理技术的实际应用,有助于学生深入理解相关知识,提升实际动手能力。

输电线不同类型短路对同步调相机转子损耗及温升的影响

同步调相机可为特高压直流换流站提供无功功率,以保持系统电压稳定,防止直流换相失败。交流系统发生短路导致系统电压降低时,调相机会向系统提供大量无功功率。然而,高无功大电流会导致调相机转子损耗和发热增加。为了研究调相机承受系统短路故障的能力,该文将调相机的电磁场、温度场模型与电网模型耦合,计算了输电线路发生单相、两相和三相短路故障时,调相机转子槽楔和铁心的损耗分布,揭示了各部分损耗密度随转子径向深度的变化规律;在此基础上计算了三种短路故障下调相机转子的温度分布,获得了转子最大温升出现的位置;在考虑转子最高容许温度的条件下,揭示了调相机短路持续时间与短路故障类型之间的关系。该研究为提高调相机在系统故障情况下的工作能力提供了理论依据。

基于FFT-LSTM的变速抽蓄机组转子绕组短路故障和偏心故障诊断方法

变速抽水蓄能机组是适应系统功率波动的重要调节手段。转子绕组短路故障和转子偏心故障是其常见的故障类型,两种故障均会在定子侧感应生成特征频带相近的谐波环流,导致两种故障难以被区分。提出了一种基于快速傅里叶变换-长短期记忆(fast Fourier transform-long short-term memory,FFT-LSTM)网络的故障诊断方法,以细化分辨故障特征相近的转子绕组短路故障和转子偏心故障。所提方法以定子分支环流的谐波分量为特征量进行故障诊断,分别推导了两种故障发生时定子侧环流谐波特征,并总结二者间的相似性和差异性。鉴于该差异较为微弱,引入长短期记忆(long short-term memory,LSTM)神经网络算法对其进行辨识。利用内部故障仿真模型对可能发生的转子绕组短路故障和偏心故障进行批量仿真,以得到用于LSTM网络训练和测试的数据集。仿真结果表明FFT-LSTM能够准确诊断不同转速下变速抽蓄机组的转子绕组短路故障和转子偏心故障。

基于端口频域特性的水轮发电机转子绕组匝间短路故障诊断

包含抽蓄发电机在内的大型水轮发电机转子为具有多匝长绕组的显极式转子,传统的基于交流阻抗测量的绕组匝间短路故障诊断方法存在灵敏性和便捷性等方面的不足。基于多导体传输线理论建立了显极式转子绕组的端口频域特性模型,通过仿真分析提出了故障判别和定位方法。最后通过真机转子的故障模拟和测试对诊断方法的有效性进行了验证。仿真和试验结果表明,所提方法能够在无需断开磁极间电气连接的测量条件下实现绕组匝间短路故障的诊断和定位。

调相机故障诊断及研究进展

同步调相机因其优秀的无功响应能力逐渐成为直流特高压(UHVDC)输电系统无功补偿设备的最优选择。新型同步调相机在使用过程中,不可避免地会出现各种故障,如绕组匝间短路故障、转子偏心故障和轴承故障等。但目前对同步调相机的故障诊断研究仍然较少。因此,本文对同步调相机的定子绕组匝间短路故障、转子绕组匝间短路故障、转子偏心故障、水路堵塞故障和轴承故障等的产生原因、故障特征和诊断方法进行了总结,并分析了各种故障诊断方法的特点,指出了同步调相机故障诊断领域存在的挑战和发展趋势。

同步调相机极限工况下典型磁场不对称故障安全风险

同步调相机典型磁场不对称故障下,由强励所形成的不平衡力和跳机风险升高。首先,分析转子动偏心和转子绕组匝间短路等典型故障对调相机磁场的影响机理;然后,借助气隙磁导法推导得到转子承受的不平衡磁拉力表达式,分析强励对不平衡电磁力的影响规律;最后,在一台大型同步电机上进行有限元电磁暂态仿真,模拟动偏心和转子绕组匝间短路故障,分别在调相正常励磁和强励工况下提取了转子所受不平衡电磁力,评估机组在强励状态下发生跳机的可能性。结果表明,强励状态下,调相机组由动偏心故障产生的不平衡磁拉力不会引起机组的剧烈振动,而转子匝间短路故障产生了较大的不平衡磁拉力,可能导致机组跳机。

抽水蓄能机组多工况下转子匝间短路故障检测效果分析

转子绕组匝间短路故障在抽水蓄能机组内部形成了不平衡磁拉力,可导致机组剧烈振动,对该故障进行精准、实时检测十分必要。针对抽水蓄能机组运行工况多变的特点,利用在机组定子铁心上安装的U型检测线圈检测转子绕组匝间短路故障,以某水电站一台322 MW抽水蓄能机组为例,通过有限元软件仿真了机组空载工况、额定负载、发电调相、电动机负载和电动调相等典型工况,模拟了不同程度的转子绕组匝间短路故障,结果表明,故障后检测线圈感应电动势中均出现了分数次谐波,且其幅值随着故障程度的加重而增大,证明了U型检测线圈在抽水蓄能机组多工况下均可以有效反映转子绕组匝间短路故障,因此,U型检测线圈法适用于抽水蓄能机组的转子匝间短路故障在线诊断。

异步机状态的能量观及其对同步发电机不对称短路的启示

从能量(功率)的角度,详尽分析了异步机全部五种状态的特征。特别值得强调的是制动状态的特征:从定子和转子两个方向汲取功率,用于转子绕组的铜耗。该铜耗转化为热能,导致转子绕组过热,甚至被烧毁。从中得到对同步发电机不对称短路的启示:负序猛于虎,千万要当心。

基于重复脉冲法的变速抽蓄机组转子绕组短路故障诊断方法

变速抽蓄机组的转子侧采用特殊的三相交流绕组结构,导致其转子绕组短路故障诊断困难。为此,提出了一种基于重复脉冲法(repetitive surge oscillograph,RSO)的离线故障诊断方法。首先设计了重复脉冲法在变速抽蓄机组中的应用方案,通过在转子三相同时注入低压脉冲并检测响应曲线来判断机组故障情况。基于不同短路故障的响应特性分析,提出了转子绕组短路故障类型和故障相别的识别方法。然后,结合变分模态分解与Teager能量算子(variational mode decomposition-teager energy operator,VMD-TEO)估计注入脉冲和特征曲线的起始突变位置,并通过时间差值和实测波速确定故障位置。最后,利用指数还原故障因子衡量匝间短路故障的严重程度,以解决克服行波衰减引起的特征波形幅值重叠问题。仿真结果表明,所提方案能准确诊断变速抽蓄机组的各种转子绕组短路故障。

一起RSO检测无效的大型隐极同步电机转子动态匝间短路故障检测与处理

发电机的安全可靠运行对电网具有重要意义。本文以某台330MW汽轮发电机为例,介绍了其启机过程中出现的轴振明显上升情况,在重复脉冲法、直流电阻、交流阻抗和功率损耗试验结果均正常的情况下,根据轴振与励磁电流相关性、励磁电流特征、轴电压及气隙探测线圈波形综合判断出转子存在动态匝间短路故障。经将转子返厂解体,发现4~8号线圈存在明显的顶匝变形现象,经修复后机组重新投入运行。本案例是典型的重复脉冲法检测无效案例,本文采用的综合检测判断方法和故障处理经验对类似机组处理具有一定的借鉴作用。

励磁绕组短路下关键运行参数差异对汽轮发电机转子动力学特性的影响

分析了励磁绕组短路下,关键运行参数差异对汽轮发电机转子动力学特性的影响。关键运行参数包括短路程度、短路位置,以及电机负载率;转子动力学特性包括转子不平衡磁拉力激励特性、径向振动响应特性,以及转子铁芯动力学响应规律。基于柔性转子不平衡磁拉力激励与振动响应的理论分析、有限元仿真计算,以及动模试验来探索不同运行参数造成动力学特性差异的规律。结果表明:正常情况下转子不平衡磁拉力趋于零,转子振动以常规基频和定子传递过来的各偶次倍频为主;励磁绕组匝间短路下,转子不平衡磁拉力及其振动响应将产生新的奇次倍频成分,且通频振动幅值增大。随着短路程度或负载的增加,转子不平衡磁拉力与振动响应的基频将增大;短路位置越靠近大齿处,转子不平衡磁拉力与振动幅值越大;转子铁芯大齿的外表面和内槽表面边沿为动力学响应的危险位置。