Transformer Mechanical Condition Assessment Method Based on Improved Grey Similarity Correlation

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.