Method for predicting remaining life of multi-source data fused aero-turbofan engine

The invention discloses a method for predicting the remaining life of a multi-source data driven aero-turbofan engine. According to the method, the remaining life of the engine is predicted by completely utilizing monitoring data acquired by an engine sensor. The method comprises four steps of estimating multi-source monitoring data fusion and failure threshold values; modeling the degradation process of the engine and estimating parameters; describing the remaining life of the engine; and predicting the remaining life. Compared with the prior art, the method has the following advantages: multi-source monitoring data is fused on the basis of common main component analysis and Euclidean distance to extract the health index and the failure threshold value representing the operating state of the engine and solve the problem that monitoring data information in the traditional prediction method is utilized incompletely; the Wiener process with nonlinear drift is established to represent the aero-engine degradation