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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 |
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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%.
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Received: 25 May 2020
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