Turbofan engine performance degradation prediction based on gas path parameter fusion

In view of the problem of low accuracy in predicting performance degradation of turbofan engine driven by a single parameter，a turbofan engine performance degradation prediction method based on gas path parameter fusion was proposed.By monitoring multi-source parameters in the process of engine performance degradation，a combination of expert experience and nuclear principal component analysis was used to select and integrate engine performance indicators to construct health parameters.The turbofan engine degradation model was constructed based on the nonlinear Wiener process，and the maximum likelihood method was used to obtain the offline parameter estimates of the engine degradation model secondly，due to the difference of performance degradation of different engines，real-time updating of random parameters based on Bayesian updating concept can realize real-time prediction of performance degradation of single engine.Finally，through the verification of examples，the root mean square error at the end of prediction using this method was 0.028 3，and the overall prediction accuracy was improved by 54.5%，which can assist in guiding maintenance decision-making.