定日镜表面风压的重构与预测

When wind tunnel test is used to research heliostat's surface wind pressure, number of measuring points usually cannot meet demand of computation, as requires interpolation prediction to obtain wind pressure time series of which where measuring points are not arranged. This article analyse heliostat's surface wind field distribution characteristics using technique of proper orthogonal decomposition (POD) method plus wind pressure time interval data synchronously collected in wind tunnel test. It's Matlab programmed according to point that POD decomposed wind pressure correlation matrix becomes time principal coordinates and spatial eigenvectors, and interfaced with Surfer software. Different interpolation methods like inverse distance method, triangulation with linear interpolation & Kriging method are selected to spatially interpolate eigenvectors to study participant mode's exponents influence on sequential accuracy of restructured wind pressure and calculate predicted points' wind pressure time series. The result indicates: restructured and surveyed wind pressure sequences gradually approaches to each other as restructuring-participant mode increases in number; among three interpolation prediction techniques, triangulation with linear interpolation and Kriging method are better than inverse distance method on forecast effect.