Research on selection method of aero-engine health parameters based on correlation and condition number

Abstract

Aiming at the problem of how to select aero-engine health parameters when the number of sensors is limited, a method of selecting aero-engine health parameters based on correlation and condition number is proposed. Firstly, the engine health parameters are preliminarily selected based on correlation. When the influence of two health parameters on engine output parameters is strongly correlated, only one of them needs to be selected. Then health parameters are further selected based on condition number of sensors parameters degradation matrixes. The larger the condition number is, the more ill conditioned the matrix is and the worse the estimation effect of the on-board model is. According to this, the combination of health parameters with the minimum condition number is selected. The proposed method can quickly select optimal health parameters and improve the accuracy of engine adaptive estimation. The results demonstrate that the stronger the correlation between the two health parameters, the greater the impact on the accuracy of the on-board model. Compared with the singular value decomposition-Kalman filter (SVD-KF) method and other combinations of health parameters, the on-board model accuracy of the optimal combination selected by this method is greatly improved, and has the best state parameter tracking effect.