V/x型牵引变压器匝间短路识别方法研究
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摘要
V/x型牵引变压器匝间短路是威胁重载货运专线牵引供电系统运行安全的重要因素,欲实现匝间故障的快速、准确识别,必须建立高效的模态特征提取方法。组合经验模态分解(EMD)和能量权重原理的多尺度能量熵识别方法,可从差动电流信号中准确提取牵引变压器匝间的动态特征信息。该方法首先对差动电流信号进行EMD分解,以获得若干固有模态函数(IMF)分量;然后计算差动电流信号和各个IMF分量的能量权重;最后构建基于能量权重的多尺度能量熵,并以熵值作为识别匝间短路的特征矢量。实验案例证明,该方法不仅能快速准确识别出变压器匝间短路,而且具有原理清晰、模式空间划分简单的优点。
The V/x traction transformer inter-turn short circuit is an important factor threatening the operation safety of the heavy-duty freight line traction power supply system(TPSS)in heavy haul freight-dedicated line.An effective modal feature extraction method must be established to achieve rapid and accurate identification of the inter-turns fault.The multi-scale energy entropy recognition method based on principles of EMD(empirical mode decomposition)and energy weight,can accurately extract the dynamic characteristic information of traction transformer windings from the differential current signal.Firstly,several intrinsic mode functions(IMF)component are obtained from differential current signal by EMD principle.Secondly,the energy weights of differential current signal and each IMF component are calculated.Finally,the multi-scale energy entropy based on energy weight is constructed,and its value is defined as the feature vector of inter-turns fault.The results show that this method not only can identify the inter-turn fault of transformer,but also has the advantages of clear principle and simple division of mode space.
The V/x traction transformer inter-turn short circuit is an important factor threatening the operation safety of the heavy-duty freight line traction power supply system(TPSS)in heavy haul freight-dedicated line.An effective modal feature extraction method must be established to achieve rapid and accurate identification of the inter-turns fault.The multi-scale energy entropy recognition method based on principles of EMD(empirical mode decomposition)and energy weight,can accurately extract the dynamic characteristic information of traction transformer windings from the differential current signal.Firstly,several intrinsic mode functions(IMF)component are obtained from differential current signal by EMD principle.Secondly,the energy weights of differential current signal and each IMF component are calculated.Finally,the multi-scale energy entropy based on energy weight is constructed,and its value is defined as the feature vector of inter-turns fault.The results show that this method not only can identify the inter-turn fault of transformer,but also has the advantages of clear principle and simple division of mode space.
引文
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[23]冯存亮,葛宝明,毕大强.三相V/V牵引变压器励磁涌流的识别[J].铁道学报,2011,33(6):35-40.
[24]关海川,高仕斌,潘育山.基于参数辨识的SCOTT变压器保护[J].高电压技术,2008,34(3):546-549.
[25]郭蕾,高仕斌,李群湛.基于模型的阻抗匹配平衡牵引变压器的保护[J].高电压技术,2008,34(3):546-549.
[26]安晓红,牛江川,任彬,等.基于Gabor变换和EMD的轴承故障诊断[J].石家庄铁道大学学报,2017,30(1):81-85.
[27]杨茂陈,郁林.基于EMD分解和集对分析的风电功率实时预测[J].电工技术学报,2016,31(621):86-93.
[2]刘玉欢,陆于平,袁宇波,等.基于磁制动原理的特高压变压器励磁涌流快速识别[J].中国电机工程学报,2007,27(34):52-58.
[3]曾麟钧,林湘宁,黄景光,等.特高压自耦变压器的建模和电磁暂态仿真[J].中国电机工程学报,2010,30(1):91-97.
[4]赵永彬,陆于平.基于磁通对称特性的变压器励磁涌流判别新算法[J].电工技术学报,2007,22(12):66-70.
[5]郝治国,张保会,褚云龙,等.基于等值回路平衡方程的变压器保护原理[J].中国电机工程学报,2012,26(10):67-72.
[6]王雪,王增平.基于波形时域分布特征的变压器励磁涌流识别[J].电工技术学报,2012,27(1):148-154.
[7]Ma J,Wang Z P,Yang Q X,et al.Identifying transformer inrush current based on normalized grille curve[J].IEEETransactions on Power Delivery,2011,26(2):588-595.
[8]Medeiros R P,Costa F B,Silva K M.Power Transformer differential protection using the boundary discrete wavelet transform[J].IEEE Transactions on Power Delivery,2016,31(5):2083-2095.
[9]Ghunem R A,El-Shatshat R,Ozgonenel O.A novel selection algorithm of a wavelet-based transformer differential current features[J].IEEE Transactions on Power Delivery,2014,29(3):1120-1126.
[10]Ozgonenel O,Karagol S.Transformer differential protection using wavelet transform[J].Electric Power Systems Research,2014,114:60-67.
[11]Guillen D,Esponda H,Vazquez E,et al.Algorithm for transformer differential protection based on wavelet correlation modes[J].IET Generation,Transmission and Distribution,2016,10(12):2871-2879.
[12]Bagheri S,Moravej Z,Gharehpetian G B.Effect of transformer winding mechanical defects,internal and external electrical faults and inrush currents on performance of differential protection[J].IET Generation,Transmission and Distribution,2017,11(10):2508-2520.
[13]Illias H A,Chai X R,Hosseinian S H,et al.Hybrid modified evolutionary particle swarm optimisation-time varying acceleration coefficient-artificial neural network for power transformer fault diagnosis[J].Measurement,2016,90:94-102.
[14]Tripathy M,Maheshwari R P,Verma H K.Power transformer differential protection based on optimal probabilistic neural network[J].IEEE Transactions on Power Delivery,2010,25(1):102-112.
[15]Etumi A A,Anayi F.The application of correlation technique in detecting internal and external faults in three-phase transformer and saturation of current transformer[J].IEEE Transactions on Power Delivery,2016,31(5):2131-2139.
[16]Saleh S M,EL-Hoshy S H,Gouda O E.Proposed diagnostic methodology using the cross-correlation coefficient factor technique for power transformer fault identification[J].IET Generation,Transmission and Distribution,2017,11(3):412-422.
[17]Masoum A S,Hashemnia N,Abu-Siada A,et al.Online transformer internal fault detection based on instantaneous voltage and current measurements considering impact of harmonics[J].IEEE Transactions on Power Delivery,2017,32(2):587-598.
[18]和敬涵,李静正,姚斌,等.基于波形正弦度特征的变压器励磁涌流判别算法[J].中国电机工程学报,2007,27(4):54-58.
[19]徐岩,王增平,杨奇逊.基于电压电流微分波形特性的变压器保护新原理的研究[J].中国电机工程学报,2004,24(2):61-65.
[20]Koley C,Purkait P,Chakravorti S.SVM classifier for impulse fault identification in transformers using fractal features[J].IEEE Transactions on Dielectrics and Electeical Insulation,2007,14(6):1538-1547.
[21]邵德军,尹项根,张哲,等.基于基波幅值增量的变压器和应涌流识别方法[J].中国电机工程学报,2010,30(10):77-83.
[22]Wu W C,Ji T Y,Li M S,et al.Using mathematical morphology to discriminate between internal fault and inrush current of transformers[J].IET Generation,Transmission and Distribution,2016,10(1):73-80.
[23]冯存亮,葛宝明,毕大强.三相V/V牵引变压器励磁涌流的识别[J].铁道学报,2011,33(6):35-40.
[24]关海川,高仕斌,潘育山.基于参数辨识的SCOTT变压器保护[J].高电压技术,2008,34(3):546-549.
[25]郭蕾,高仕斌,李群湛.基于模型的阻抗匹配平衡牵引变压器的保护[J].高电压技术,2008,34(3):546-549.
[26]安晓红,牛江川,任彬,等.基于Gabor变换和EMD的轴承故障诊断[J].石家庄铁道大学学报,2017,30(1):81-85.
[27]杨茂陈,郁林.基于EMD分解和集对分析的风电功率实时预测[J].电工技术学报,2016,31(621):86-93.