Winding Deformation Detection Based on Distributed Optical Fiber Sensing
Liu Yunpeng1,2, Li Huan1,2, Tian Yuan3, He Peng4, Fan Xiaozhou1,2
1. State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources North China Electric Power University Beijing 102206 China; 2. Hebei Provincial Key Laboratory of Power Transmis-sion Equipment Security Defense North China Electric Power University Baoding 071003 China; 3. State Grid Hebei Electric Power Research Institute Shijiazhuang 050021 China; 4. State Grid Hebei Electric Power Co. Ltd Shijiazhuang Power Supply Company Shijiazhuang 050021 China
Abstract：In order to locate and evaluate the radial deformation of transformer windings, distributed optical fiber sensing technology is applied to the field of online transformer winding deformation detection. A shallow groove is cut on the surface of the copper wire, where two sensing fibers are arranged to produce a fiber composite wire. The electrostatic field simulation was carried out using COMSOL Multiphysics, and the results showed that compared with normal wires, there was no obvious electric field distortion or insulation strength decrease. The simulation of solid mechanics was also carried out, the results of which showed that under both concave and convex deformation conditions, the relationship between fiber strain and wire deformation (taking deflection as an index) can be described by a quadratic function, R2>0.999. Then, the actual windings were simulated using copper bars pasted with fibers, and a test platform was built on the basis of the simulation conclusions to obtain the relationship between the winding deflection and the Brillouin frequency shift. Finally, a 35kV continuous winding prototype was wound with fiber-composite wire s. Using this winding, with the help of brillouin optical time domain reflection (BOTDR) technology, accurate positioning of the deformation was completed, with an accuracy within 1 turn.The determination of deformation degree is also implemented, with an error less than 10%.
刘云鹏, 李欢, 田源, 贺鹏, 范晓舟. 基于分布式光纤传感的绕组变形程度检测[J]. 电工技术学报, 2021, 36(7): 1347-1355.
Liu Yunpeng, Li Huan, Tian Yuan, He Peng, Fan Xiaozhou. Winding Deformation Detection Based on Distributed Optical Fiber Sensing. Transactions of China Electrotechnical Society, 2021, 36(7): 1347-1355.
[1] 刘旸, 周志强, 陈浩. 大型电力变压器短路事故分析与反事故措施[J]. 东北电力技术, 2015, 36(5): 30-32. Liu Yang, Zhou Zhiqiang, Chen Hao.Analysis and countermeasures of short-circuit accidents of large power transformers[J]. Northeast Electric Power Technology, 2015, 36(5): 30-32. [2] 中国电力科学研究院. 国家电网公司变压器抗短路研究报告[R]. 北京: 中国电力科学研究院, 2006. China Electric Power Research Institute. State Grid Corporation transformer short circuit research report[R]. Beijing: China Electric Power Research Institute, 2006. [3] 赵义焜, 张国强, 韩冬, 等. 高频变压器用匝间绝缘材料沿面放电特性的实验研究[J]. 电工技术学报, 2019, 34(16): 3464-3471. Zhao Yikun, Zhang Guoqiang, Han Dong, et al.Study on surface discharge characteristics of inter-turn insulation materials in high-frequency transformers[J]. Transactions of China Electrotechnical Society, 2019, 34(16): 3464-3471. [4] 沈明, 尹毅, 吴建东, 等. 变压器绕组变形在线监测实验研究[J]. 电工技术学报, 2014, 29(11): 184-190. Shen Ming,Yin Yi, Wu Jiandong, et al.Experimental investigating on on-line monitoring of winding deformation of power transformers[J]. Transactions of China Electrotechnical Society, 2014, 29(11): 184-190. [5] 赵仲勇, 唐超, 李成祥, 等. 基于频率响应二值化图像的变压器绕组变形故障诊断方法[J]. 高电压技术, 2019, 45(5): 1526-1534. Zhao Zhongyong, Tang Chao, Li Chengxiang, et al.Diagnosis method of transformer winding deformation faults based on frequency response binary image[J]. High Voltage Engineering, 2019, 45(5): 1526-1534. [6] 李成祥, 夏麒, 朱天宇, 等. 基于脉冲频率响应法的变压器绕组变形带电检测仪[J]. 电力自动化设备, 2018, 38(1): 110-115,120. Li Chengxiang, Xia Qi, Zhu Tianyu, et al.Live transformer winding deformation detector based on impulse frequency response method[J]. Electric Power Automation Equipment, 2018, 38(1): 110-115, 120. [7] 刘勇, 汲胜昌, 杨帆, 等. 检测变压器故障的扫频阻抗法特性研究及应用[J]. 高电压技术, 2016, 42(10): 3237-3245. Liu Yong, Ji Shengchang, Yang Fan, et al.Characteristics and application of sweep frequency impedance method for detecting transformer fault[J]. High Voltage Engineering, 2016, 42(10): 3237-3245. [8] 刘勇, 杨帆, 张凡, 等. 检测电力变压器绕组变形的扫频阻抗法研究[J]. 中国电机工程学报, 2015, 35(17): 4505-4516. Liu Yong, Yang Fan, Zhang Fan, et al.Research on sweep frequency impedance method for detecting winding deformation of power transformer[J]. Proceedings of the CSEE, 2015, 35(17): 4505-4516. [9] 张旭苹. 全分布式光纤传感技术[M]. 1版. 北京: 科学出版社, 2013. [10] 周延辉, 赵振刚, 李英娜, 等. 埋入35kV干式空心电抗器的光纤布拉格光栅测温研究[J]. 电工技术学报, 2015, 30(5): 142-146. Zhou Yanhui, Zhao Zhengang, Li Yingna, et al.The study on the temperature measurement for the 35 kV dry-type air-core reactor with the embedded optical fiber Bragg grating[J]. Transactions of China Electrotechnical Society, 2015, 30(5): 142-146. [11] 孟令健. 缠绕式光纤应变传感器开发及在道路工程中的应用[D]. 北京: 北京科技大学, 2019. [12] 董鹏, 夏开文, 于长一, 等. 浅埋隧道覆岩变形沉降的分布式光纤监测与分析[J]. 防灾减灾工程学报, 2019, 39(5): 724-732. Dong Peng, Xia Kaiwen, Yu Changyi, et al.Distributed optical fiber monitoring and analysis of deformation and settlement of cover rock in shallow tunnels[J]. Journal of Disaster Prevention and Mitigation Engineering, 2019, 39(5): 724-732. [13] 王鹤, 李兴宝, 路俊海, 等. 基于叠加原理的光纤复合低压电缆热路模型建模[J]. 电工技术学报, 2019, 34(7): 1381-1391. Wang He, Li Xingbao, Lu Junhai, et al.Modeling method of OPLC thermal circuit model based on superposition principle[J]. Transactions of China Electrotechnical Society, 2019, 34(7): 1381-1391. [14] 刘云鹏, 步雅楠, 田源, 等. 基于分布式光纤传感的变压器绕组变形检测与故障识别可行性研究[J]. 高电压技术, 2019, 45(5): 1483-1489. Liu Yunpeng, Bu Yanan, Tian Yuan, et al.Feasibility study on transformer winding deformation detection and fault identification based on distributed optical fiber sensing[J]. High Voltage Engineering, 2019, 45(5): 1483-1489. [15] Liu Yunpeng, Tian Yuan, Fan Xiaozhou, et al.Detection and identification of transformer winding strain based on distributed optical fiber sensing[J]. Applied Optics, 2018, 57(22): 6430-6438. [16] 张书琦, 普天, 向李程, 等. 变压器绕组线光纤嵌入过程的应变监测[J]. 光通信技术, 2020, 44(7): 52-55. Zhang Shuqi, Pu Tian, Xiang Licheng, et al.Strain monitoring of transformer winding wire fiber embedding process[J]. Optical Communication Technology, 2020, 44(7): 52-55. [17] 权志桥, 方新秋, 薛广哲, 等. 表面粘贴布拉格光纤光栅传感器的应变传递耦合机理研究[J]. 中国激光, 2020, 47(1): 163-172. Quan Zhiqiao, Fang Xinqiu, Xue Guangzhe, et al.Strain transfer coupling mechanism of surface-bonded fiber Bragg grating sensor[J]. Chinese Journal of Lasers, 2020, 47(1): 163-172. [18] 周延辉, 赵振刚, 李英娜, 等. 光纤光栅在干式空心电抗器固化中的应变监测研究[J]. 电工技术学报, 2015, 30(13): 27-31. Zhou Yanhui, Zhao Zhengang, Li Yingna, et al.Strain monitoring with fiber grating for dry-type air-core reactor solidification[J]. Transactions of China Electrotechnical Society, 2015, 30(13): 27-31. [19] 章征林, 高磊, 孙阳阳, 等. 分布式光纤传感器应变传递规律研究[J]. 中国激光, 2019, 46(4): 285-293. Zhang Zhenglin, Gao Lei, Sun Yangyang, et al.Strain transfer law of distributed optical fiber sensor[J]. Chinese Journal of Lasers, 2019, 46(4): 285-293. [20] 田源. 基于分布式光纤传感的变压器绕组变形检测方法研究[D]. 北京: 华北电力大学(北京), 2019. [21] 董玉明, 张旭苹, 路元刚, 等. 布里渊散射光纤传感器的交叉敏感问题[J]. 光学学报, 2007(2): 197-201. Dong Yuming, Zhang Xuping, Lu Yuangang, et al.Cross sensitivity of Brillouin scattering distributed fiber sensor[J]. Acta Optica Sinica, 2007, 27(2): 197-201. [22] Liu Xuan, Bao Xiaoyi.Brillouin spectrum in LEAF and simultaneous temperature and strain measurement[J]. Journal of Lightwave Technology, 2012, 30(8): 1053-1059. [23] Gao Shuguo, Liu Yunpeng, Li Huan, et al.Transformer winding deformation detection based on BOTDR and ROTDR[J]. Sensors, 2020, 20(7): 2062. DOI:10.3390/s20072062. [24] 杜江, 孙铭阳. 基于变权灰云模型的变压器状态层次评估方法[J]. 电工技术学报, 2020, 35(20): 4306-4316. Du Jiang, Sun Mingyang.Hierarchical assessment method of transformer condition based on weight-varying grey cloud model[J]. Transactions of China Electrotechnical Society, 2020, 35(20): 4306-4316. [25] 梁得亮, 柳轶彬, 寇鹏, 等. 智能配电变压器发展趋势分析[J]. 电力系统自动化, 2020, 44(7) : 1-14. Liang Deliang, Liu Yibin, Kou Peng, et al.Analysis of development trend for intelligent distribution transformer[J]. Automation of Electric Power Systems, 2020, 44(7):1-14.
2021, Vol. 36 
