基于动车组车载变压器频率响应优化模型的故障定位Fault Location Based on Frequency Response Optimization Model of EMU On-Board Transformer
吴振宇;周利军;王东阳;张桂南;于兴宇;江飞明;周猛;
摘要(Abstract):
高速铁路动车组车载变压器采用单相分裂式绕组结构,4组高压绕组在油箱内部并联连接,导致无法独立测量各组的频率响应曲线,从而无法确定故障绕组。为解决上述问题,联合MATLAB软件与Maxwell软件,建立并验证考虑绕组相间电容的车载变压器频率响应优化模型;基于优化模型模拟不同故障绕组下多端口频率响应曲线演变规律,同时结合多条频率响应曲线的特征谐振点偏移规律识别故障绕组,解析故障绕组定位步骤,并进行故障模拟验证。结果表明:当靠近铁芯的外层牵引绕组出现故障时,高压绕组频率响应曲线不发生变化,但牵引绕组频率响应曲线变化显著,而当其他绕组出现故障时,高压绕组频率响应曲线均发生变化;当高压绕组出现故障时,牵引绕组频率响应曲线的第一谐振点和第二谐振点均向右偏移,而第三谐振点几乎不变;当远离铁芯的内层牵引绕组出现故障时,牵引绕组频率响应曲线的第一谐振点与第二谐振点均向左偏移,而第三谐振点则向右偏移。
关键词(KeyWords): 车载变压器;分裂式绕组;频率响应法;有限元;轴向移位;故障定位;谐振点
基金项目(Foundation): 国家自然科学基金高铁联合基金资助项目(U1834203);; 四川省科技计划项目(2020JDTD0009);; 广东省基础与应用基础研究基金资助项目(2020B1515130001);; 中国铁道科学研究院集团有限公司院基金课题(2020YJ082)
作者(Authors): 吴振宇;周利军;王东阳;张桂南;于兴宇;江飞明;周猛;
参考文献(References):
- [1]王华胜.动车组整车可靠性的验证方法[J].中国铁道科学,2010,31(3):82-86.(WANG Huasheng. Reliability Verification Method of the Whole Electric Multiple Unit[J]. China Railway Science,2010,31(3):82-86. in Chinese)
- [2]田长海.发展中的我国铁路列车速度、密度、重量[J].中国铁道科学,2020,41(4):127-135.(TIAN Changhai. China's Railway Train Speed,Density and Weight in Developing[J]. China Railway Science,2020,41(4):127-135. in Chinese)
- [3]孙丽霞,李晓峰,胡晓依,等.高速动车组车轮磨耗对轮轨接触关系及车辆动力学性能的影响[J].中国铁道科学,2020,41(6):117-126.(SUN Lixia,LI Xiaofeng,HU Xiaoyi,et al. Influence of Wheel Wear on Wheel-Rail Contact Relationship and Vehicle Dynamic Performance of High-Speed EMU[J]. China Railway Science,2020,41(6):117-126. in Chinese)
- [4] SHI Y H,JI S C,ZHANG F,et al. Application of Operating Deflection Shapes to the Vibration-Based Mechanical Condition Monitoring of Power Transformer Windings[J]. IEEE Transactions on Power Delivery,2021,36(4):2164-2173.
- [5] SHI Y H,JI S C,ZHANG F,et al. Multi-Frequency Acoustic Signal under Short-Circuit Transient and Its Application on the Condition Monitoring of Transformer Winding[J]. IEEE Transactions on Power Delivery,2019,34(4):1666-1673.
- [6]徐建源,陈彦文,李辉,等.基于短路电抗与振动信号联合分析的变压器绕组变形诊断[J].高电压技术,2017,43(6):2001-2006.(XU Jianyuan,CHEN Yanwen,LI Hui,et al. Transformer Winding Deformation Analysis Based on Short-Circuit Reactance and Vibration Signal Analysis[J]. High Voltage Engineering,2017,43(6):2001-2006. in Chinese)
- [7] DICK E P,ERVEN C C. Transformer Diagnostic Testing by Frequency Response Analysis[J]. IEEE Transactions on Power Apparatus and Systems,1978,PAS-97(6):2144-2153.
- [8] IEC. IEC 60076-18—2012 Power Transformers—Part 18:Measurement of Frequency Response[S]. Geneva:International Electro Technical Commission,2012.
- [9] IEEE. IEEE Std C57.149—2012 IEEE Guide for the Application and Interpretation of Frequency Response Analysis for Oil-Immersed Transformers[S]. New York:IEEE Power and Energy Society,2013.
- [10]国家能源局. DL/T 911—2016电力变压器绕组变形的频率响应分析法[S].北京:中国电力出版社,2016.(National Energy Bureau of the People's Republic of China. DL/T 911—2016 Frequency Response Analysis on Winding Deformation of Power Transformers[S]. Beijing:China Electric Power Press,2016. in Chinese)
- [11] JIANG J F,ZHOU L J,GAO S B,et al. Frequency Response Features of Axial Displacement Winding Faults in Autotransformers with Split Windings[J]. IEEE Transactions on Power Delivery,2018,33(4):1699-1706.
- [12]梁贵书,张喜乐,王晓晖,等.特快速暂态过电压下变压器绕组高频电路模型的研究[J].中国电机工程学报,2006,26(4):144-148.(LIANG Guishu,ZHANG Xile,WANG Xiaohui,et al. Research on High-Frequency Circuit Model of Transformer Windings in VFTO[J]. Proceedings of the CSEE,2006,26(4):144-148. in Chinese)
- [13] HASHEMNIA N,ABU-SIADA A,ISLAM S. Improved Power Transformer Winding Fault Detection Using FRA Diagnostics—Part 1:Axial Displacement Simulation[J]. IEEE Transactions on Dielectrics and Electrical Insulation,2015,22(1):556-563.
- [14] HASHEMNIA N,ABU-SIADA A,ISLAM S. Improved Power Transformer Winding Fault Detection Using FRA Diagnostics—Part 2:Radial Deformation Simulation[J]. IEEE Transactions on Dielectrics and Electrical Insulation,2015,22(1):564-570.
- [15] ZHAO Z Y,YAO C G,LI C X,et al. Detection of Power Transformer Winding Deformation Using Improved FRA Based on Binary Morphology and Extreme Point Variation[J]. IEEE Transactions on Industrial Electronics,2018,65(4):3509-3519.
- [16] ALJOHANI O,ABU-SIADA A. Application of Digital Image Processing to Detect Short-Circuit Turns in Power Transformers Using Frequency Response Analysis[J]. IEEE Transactions on Industrial Informatics,2016,12(6):2062-2073.
- [17] ZHOU L J,LIN T,ZHOU X Y,et al. Detection of Winding Faults Using Image Features and Binary Tree Support Vector Machine for Autotransformer[J]. IEEE Transactions on Transportation Electrification,2020,6(2):625-634.
- [18] WU Z Y,ZHOU L J,WANG D Y,et al. Feature Analysis of Oscillating Wave Signal for Axial Displacement in Autotransformer[J]. IEEE Transactions on Instrumentation and Measurement,2021,70:1-13.
- [19] TARIMORADI H,GHAREHPETIAN G B. Novel Calculation Method of Indices to Improve Classification of Transformer Winding Fault Type,Location,and Extent[J]. IEEE Transactions on Industrial Informatics,2017,13(4):1531-1540.
- [20]吴振宇,周利军,周祥宇,等.基于振荡波的变压器绕组故障诊断方法研究[J].中国电机工程学报,2020,40(1):348-357,401.(WU Zhenyu,ZHOU Lijun,ZHOU Xiangyu,et al. Research on Fault Diagnosis Method of Transformer Winding Based on Oscillatory Wave[J]. Proceedings of the CSEE,2020,40(1):348-357,401. in Chinese)
- [21] WU Z Y,ZHOU L J,LIN T,et al. A New Testing Method for the Diagnosis of Winding Faults in Transformer[J].IEEE Transactions on Instrumentation and Measurement,2020,69(11):9203-9214.