可再生能源2024，Vol.42Issue(5)：627-633,7.
基于MTF-Swin Transformer的风机齿轮箱故障诊断
Fault diagnosis of wind turbine gearbox based on MTF-Swin Transformer
摘要
Abstract
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.关键词
马尔科夫变迁场(MTF)/Swin Transformer/风机齿轮箱/故障诊断Key words
Markov Transition Field/Swin Transformer/wind turbine gear box/fault diagnosis分类
能源与动力引用本文复制引用
张彬桥,雷钧,万刚..基于MTF-Swin Transformer的风机齿轮箱故障诊断[J].可再生能源,2024,42(5):627-633,7.基金项目
国家自然科学基金面上项目(52077120). （52077120）
