Aero-engine combustion regulation system anomaly detection method and system based on multivariate time sequence regression model

The invention relates to the technical field of fuel oil regulation detection, in particular to an aero-engine fuel oil regulation system anomaly detection method and system based on a multivariate time sequence regression model, and the method comprises the steps: obtaining dimension data corresponding to a plurality of monitoring units during the operation of an aero-engine fuel oil regulation system; acquiring an encoder in the VAE network as a long time sequence feature extractor of the overall multivariate time sequence regression model; acquiring long time sequence characteristics; obtaining a trained multivariate time sequence regression model; obtaining a regression prediction result of the key feature dimension of the combustion regulation system at each moment; and judging the abnormity of the to-be-detected data according to the regression prediction result of the key feature dimension of the combustion regulation system at each moment. According to the method, the encoder in the VAE network is com