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Transformer Mechanical Condition Assessment Method Based on Improved Grey Similarity Correlation
ID：263 View Protection：ATTENDEE Updated Time：2022-05-19 11:13:51 Hits：295 Poster Presentation

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Abstract
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.
Keywords
transformer; vibration signal; mechanical condition; improved grey similarity correlation
Speaker
JuPing
山东大学

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Important Date

  • Conference Date

    May 27

    2022

    to

    May 29

    2022

  • Feb 28 2022

    Draft paper submission deadline

  • May 29 2022

    Registration deadline

  • Jun 22 2022

    Contribution Submission Deadline

Sponsored By
IEEE Beijing Section
China Electrotechnical Society
Southeast University
Supported By
IEEE Industry Applications Society
IEEE Nanjing Section
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