To solve the difficulty of calculating and predicting important monitoring parameter exhaust gas temperature margin (EGTM)

an EGTM calculation method and remaining life prediction model based on data were established according to the aviation industry standard implementation guidelines. The influencing factors of EGTM were split and the fan speed and exhaust temperature based on the revised similarity theory were corrected. The discrete test data of partial conversion/correction formula parameters were fitted to obtain the relationship curve. Support vector machines were used to learn the influencing factors of the engine bleed system

and the genetic algorithm was used to optimize the penalty factors and the kernel function parameter of the support vector machine to obtain EGTM parameter corrected by the engine bleed system; again

the wavelet transform was used to reduce the noise and feature extraction of the EGTM. The polynomial regression was used to fit the feature parameter to determine the single engine/average fleet EGTM performance decline rate

and the remaining life of EGTM was calculated. The model realized the whole process of calculation from data input to remaining life prediction. The EGTM calculation results had a goodness of fit up to 0994 compared with the results provided by original equipment manufacturer. Compared with the EGTM curve after wavelet transform

the fitting effect of the margin remaining life decay curve was 098. The results can be used as the theoretical support and reference basis for maintenance plan formulation and economic cost calculation.