Paper
19 October 2023 A novel method of transformer winding deformation detection
Xiaoxiao Luo, Qian Wang, Yingkai Long, Xiping Jiang, Siquan Li
Author Affiliations +
Proceedings Volume 12709, Fourth International Conference on Artificial Intelligence and Electromechanical Automation (AIEA 2023); 127094G (2023) https://doi.org/10.1117/12.2685089
Event: Fourth International Conference on Artificial Intelligence and Electromechanical Automation (AIEA 2023), 2023, Nanjing, China
Abstract
Power transformer is an important equipment in the power grid, and its health directly affects the stability of the power grid. Therefore, it is necessary to monitor the operation of the transformer to avoid accidents affecting the stability of the power grid. Transformer winding deformation detection is an important means of transformer health detection, which can directly reflect the transformer winding condition. But online monitoring of transformer winding deformation cannot be completed at present. According to the principle of transformer winding deformation detection, this paper designs a bushing with built-in sensor, which can also measure overvoltage signal. Then the feasibility of the design is verified by establishing the bushing equivalent circuit model and overvoltage measurement simulation model, which provides a new idea for online monitoring of transformer winding deformation.
© (2023) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Xiaoxiao Luo, Qian Wang, Yingkai Long, Xiping Jiang, and Siquan Li "A novel method of transformer winding deformation detection", Proc. SPIE 12709, Fourth International Conference on Artificial Intelligence and Electromechanical Automation (AIEA 2023), 127094G (19 October 2023); https://doi.org/10.1117/12.2685089
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KEYWORDS
Transformers

Deformation

Sensors

Pulse signals

Capacitance

Frequency response

Power grids

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