Fault diagnosis of wind turbine gearbox based on MTF-Swin Transformer
In response to the challenge posed by the limited accuracy of traditional fault diagnosis methods in wind turbine gearbox applications due to the complex and variable operational conditions and the presence of significant noise,the MTF-Swin Transformer wind turbine gearbox fault diagnosis model is proposed.Initially,the one-dimensional vibration time series signal is transformed into a two-dimensional feature map with correlated temporal information using the Markov Transition Field(MTF)graph encoding method.Subsequently,this feature map is employed as the input for the Swin Transformer model,which utilizes a self-attention mechanism for automatic feature extraction.This process culminates in the classification of various fault types.The results demonstrate a fault diagnosis accuracy of 99.48%,affirming the effectiveness and superiority of the proposed method.
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