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Transformer Mechanical Condition Assessment Method Based on Improved Grey Similarity Correlation
编号：263 访问权限：仅限参会人 更新：2022-05-19 11:13:51 浏览：144次 张贴报告

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摘要
Transformer mechanical condition assessment methods based on transformer vibration signals have received a lot of attention due to their non-stop, safe and other characteristics. At present, many studies of transformer body vibration signals are based on their amplitude, which has a high mistaken judgment rate. At the same time, for different loads and types of transformers, their single frequency varies widely, making it difficult to reflect the mechanical condition of the transformer effectively. In this paper, the energy share of the vibration signal is calculated in frequency bands according to the vibration characteristics of the transformer body to reduce the influence of signal fluctuations in low frequency bands on the assessment of the mechanical condition. Combining the energy distribution and frequency components of the vibration signal in different frequency bands, an improved grey similarity correlation is used to assess the mechanical condition of the transformer.
关键词
transformer; vibration signal; mechanical condition; improved grey similarity correlation
报告人
JuPing
山东大学

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重要日期

  • 会议日期

    05月27日

    2022

    至

    05月29日

    2022

  • 02月28日 2022

    初稿截稿日期

  • 05月29日 2022

    注册截止日期

  • 06月22日 2022

    报告提交截止日期

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IEEE Beijing Section
China Electrotechnical Society
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