关键词: 排气温度, 粗大误差剔除, 噪声级估计, 简单非线性去噪, 正则化, 主成分回归估计

Abstract: It is difficult to improve the prediction accuracy of the engine Exhaust Gas Temperature（EGT） effectively, aiming at this problem, a regularization chaotic prediction algorithm based on the nonlinear noise-reduction is proposed. To eliminate the impacts of other factors and outliers, data pretreatment for the actual measurement data is studied. As the prediction accuracy of EGT is affected by the noise in the measurement data and chaotic phase space reconstruction parameters, the method of using search algorithm is proposed to find the nonlinear noise-reduction parameters and the delay time and embedding dimensional of phase space which obtain better prediction accuracy of EGT. The simulation results show that the proposed prediction method is applied to predict the EGT of aeroengine, and the test results are satisfactory.

Key words: Exhaust Gas Temperature（EGT）, eliminate gross errors, determination of the noise level, simple nonlinear noise-reduction method, regularization, principal component regression estimation