基于多源数据融合的翼型表面压强精细化重构方法

Laying out pressure taps on the surface of the wind tunnel test model is an important means to obtain the surface pressure distribution. However, due to the limited space location and experimental cost, it is usually difficult to arrange enough pressure taps on the complex model surface to obtain complete surface pressure distribution information. Hence, the accuracy of the lift and moment calculated by the direct integration may fail to meet expectations. In this paper, to obtain the high-precision pressure distribution through less pressure test data, a method of combining the sparse wind tunnel test data and the numerical simulation data is proposed. Firstly, the proper orthogonal decomposition （POD） technique is used to extract the low-dimensional feature of the pressure distribution of the numerical simulation data, which is called the POD basis. Then, by applying the compressed sensing algorithm, the coordinates of the basis function are obtained with the sparse wind tunnel pressure measurement data, and finally transformed into the physical space to reconstruct the pressure distribution. The accuracy of the method is verified by the steady fixed airfoil variable state or with variable geometry in conjunction with variable flow state examples, and the reconstructed results can accurately match the experimental results. The developed reconstruction method largely solves the problem of fine reconstruction of distributed load under the condition of limited space and sparse observation.