关键词: 航空发动机;性能预测;时间序列预测+;支持向量回归+;模型

Abstract: In order to improve forecasting accuracy of aeroengine performance, a novel forecasting method based on support vector machines was presented and used to forecast performance synthetic exponent characterized the whole performance of engine. Therefore, a single-step and a multi-step forecasting model based on support vector machines was built and used to forecast performance synthetic exponent of a normal and an abnormal engine. Moreover, forecasting results are compared to those of AR model. The comparison results show that accuracy of forecasting model based on support vector regression is higher than that of AR model. For example, its four step forecasting accuracy is increased from 80.56% to 88.51%. It is suggested that forecasting model based on support vector regression is especially suitable to middle intervals or long intervals forecasting of aeroengine performance.

Key words: Aircraft engine;Performance prediction;Time series forecasting~+;Support vector machines~+;Model