To study fault prediction methods for wind turbines based on SCADA data, the SCADA data of a 2 000 kW doubly-fed wind turbine over 14 months is used as the research subject. First, the data is preprocessed to ensure its usability. Considering the issues with the traditional Transformer model, such as complex structure and numerous parameter settings, a Transformer model is constructed by introducing a linear decoder structure. This model is then used for fault prediction research on wind turbines. The study shows that the constructed algorithm model has long-term stability, can eliminate false predictions, and can predict faults 6 days in advance, providing a safeguard to prevent sudden shutdowns due to fault deterioration.