A multi-scale hybrid attention mechanism modeling method for aero-engine remaining useful life prediction belongs to the field of health management and prediction technology for aero-engines. Firstly, preprocess the data to obtain the sample, set the RUL label, and obtain the true value of the remaining useful life of the sample. Secondly, a multi-scale hybrid attention mechanism model consisting of position encoding layer, feature extraction layer, and regression prediction layer is constructed. Thirdly, train the model, and make the difference between the predicted value output by the model and the true value of the remaining useful life by minimizing the loss function until it reaches the stop standard. Finally, use the trained model to predict the remaining useful life. The method can achieve full fusion of information from different time steps of a single sample, taking into account the correlation between all samples.
A MULTI-SCALE HYBRID ATTENTION MECHANISM MODELING METHOD FOR AERO-ENGINE REMAINING USEFUL LIFE PREDICTION
2025-01-16
Patent
Electronic Resource
English
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