Aircraft engine performance parameter prediction based on ensemble ELM model

Abstract

Abstract:

In order to predict performance parameters of aircraft engine accurately, a dynamic ensemble extreme learning machine (ELM)model is proposed. Ada Boost.RT algorithm is used to integrate ELM to construct the ensemble model. Aiming at the limitation of static threshold in original AdaBoost.RT algorithm, a self-adaptive and dynamic adjusting method is used to improve the forecasting precision. A given method makes adjustments to the threshold by comparing RMSE of two neighboring iterations. Finally, compared with single ELM model and original ensemble ELMmodel, dynamic ensemble ELM model is used to predict EGTM. Results show that the improved model is better than other models for the performance parameters prediction of aircraft engine.

Key words: aircraft engine, performance parameters, prediction, AdaBoost.RT, extreme learning machine

CLC Number:

V235.13

XU Jianxin, HOU Zhenhua. Aircraft engine performance parameter prediction based on ensemble ELM model[J]. .

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Aircraft engine performance parameter prediction based on ensemble ELM model

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