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Research progress on oil-immersed transformer mechanical condition identification based on vibration signals

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  • Sun, YongTeng
  • Ma, HongZhong

Abstract

In recent years, vibration signals have been widely applied for the identification of mechanical states in oil-immersed transformers. This paper, following the framework of ‘vibration generation – sensing – processing – recognition – evaluation – solution,’ introduces the progress in mechanical state recognition of oil-immersed transformers based on vibration signals from a novel sensor-oriented perspective, which covers sensor deployment, sensor specialization, and equipment integration. The advancements in signal processing and feature selection are also discussed and compared with the identification of states in rotating machinery. To Address challenges like limited rule transferability and the weakness in vibration characteristics and models, some emerging technologies such as Operational Modal Analysis and multisource data fusion are introduced, which may bring new prospects. This paper aims to provide scholars engaged in research on the mechanical state identification of transformers and other electrical equipment with some technical references.

Suggested Citation

  • Sun, YongTeng & Ma, HongZhong, 2024. "Research progress on oil-immersed transformer mechanical condition identification based on vibration signals," Renewable and Sustainable Energy Reviews, Elsevier, vol. 196(C).
    • Handle: RePEc:eee:rensus:v:196:y:2024:i:c:s1364032124000509
    DOI: 10.1016/j.rser.2024.114327
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    References listed on IDEAS

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    1. Jaroslaw Gielniak & Magdalena Czerniak, 2021. "Investigation of Distribution Transformers Vibrations in Terms of Core and Winding Condition Assessment," Energies, MDPI, vol. 15(1), pages 1-18, December.
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