Study on technology of engine exhaust gas temperature margin prediction

The aviation safety status is more prominent and important with the development of aircraft. The aero engine is the system with the highest failure rate and maximum maintenance workload. The exhaust gas temperature is one of the performance parameters which reflected aero-engine operation state mostly. The methods of combining RBFPN (radial basis function prediction network) and FAR (functional coefficient autoregressive model) and wavelet process neural network analysis are used to make the EGTM prediction. They both get the better results.