An aerial electromechanical equipment residual life prediction method, device, medium and product fusing multi-source sensor data

Abstract

The application discloses an aviation electromechanical equipment residual life prediction method and device fusing multi-source sensor data, a medium and a product, and relates to the technical field of intelligent information. The method comprises the following steps: inputting the preprocessed multi-source sensor data of the aviation electromechanical equipment into an aviation electromechanical equipment residual life prediction model to obtain an aviation electromechanical equipment residual life prediction value; the aviation electromechanical equipment residual life prediction model is obtained by training a neural network model using a training set; the training set comprises a plurality of preprocessed training samples and corresponding aviation electromechanical equipment residual life values, and the training sample is historical multi-source sensor data; wherein the aviation electromechanical equipment residual life prediction model comprises an improved mixed bidirectional long short-term memory network submodel, a residual network submodel, a multi-head attention mechanism network submodel, a first full connection layer, a second full connection layer and a first activation function layer connected in sequence. The application improves the accuracy of aviation electromechanical equipment residual life prediction.

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