Feasibility Study on Transformer Winding Deformation Detection and Fault Identification Based on Distributed Optical Fiber Sensing

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. © 2019, High Voltage Engineering Editorial Department of CEPRI. All right reserved.