Feasibility Study on Transformer Winding Deformation Detection and Fault Identification Based on Distributed Optical Fiber Sensing
刘云鹏1,2, 步雅楠2, 田源2, 贺鹏2, 范晓舟2
1. 新能源电力系统国家重点实验室(华北电力大学),保定071003
2. 华北电力大学河北省输变电设备安全防御重点实验室,保定071003
LIU Yunpeng1,2, BU Yanan2, TIAN Yuan2, HE Peng2, FAN Xiaozhou2
1. State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Baoding 071003, China
2. Hebei Provincial Key Laboratory of Power Transmission Equipment Security Defense, North China Electric Power University, Baoding 071003, China
基金项目:
国家电网公司科技项目(524625160020);
中央高校基本科研业务费专项(2016XS93;
2017MS102);
Project supported by Science and Technology Program of SGCC (524625160020), the Central University Basic Scientific Research Business Special Funds (2016XS93, 2017MS102);
Winding distortion is a common faults inside the transformer. The traditional mature detecting method of winding deformation belongs to off-line detection, and can not judge the winding deformation mode. According to the above reasons, this paper proposes a detecting method of transformer winding deformation based on distributed optical fiber sensing. The built-in distributed optical fiber continuous winding model is used to simulate the winding deformation in practical operation. When the winding is partially deformed, the optical fiber strain will be measured by Brillouin optical time domain reflectometer (BOTDR). At last, the extreme learning machine (ELM) will make mode recognization to the detection signal. According to experimental results, the distributed optical fiber has some prestress in the winding, and the variation of fiber strain curve corresponds to different winding deformation. The accuracy of ELM is more than 90% for the winding and different deformation forms. The distributed optical fiber sensing technology can effectively detect the transformer winding deformation, which-provides a new idea for on-line monitoring of transformer winding deformation.
KEY WORDS :transformer winding deformation;online monitoring;distributed fiber;Brillouin optical time domain reflectometer;pattern recognition;extreme learning machine;
0 引言
电力变压器在电力系统中具有重要地位,其安全运行直接影响着供电的可靠性与安全性[1]。当变压器发生短路故障时,变压器绕组受到巨大电动力作用,会发生塌陷、鼓包等永久性变形[2-3]。如不及时发现,累计效应会使变形进一步加剧,最终导致变压器事故。变压器绕组变形最直观的检测方式为吊罩检查,作为早期绕组变形的检测手段,该方法耗费大量的物力和财力,且难以判断内侧绕组的状况[4]。后来,国内外专家陆续开发了多种变压器绕组变形无损检测方法。主要有短路阻抗法(short-circuit reactance, SCR)[5-6]、低压脉冲法(low voltage impulse, LVI)[7]、频率响应分析法(frequency response analysis, FRA)[8]和振动法[9]。
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