本征正交分解在数据处理中的应用及展望

Proper orthogonal decomposition (POD ) is one of the effective methods to reduce dimension of high- dimensional complex nonlinear systems. This paper summarizes research of POD method in dimension reduction in various practical engineering fields. Firstly, development history of POD method is briefly introduced, and claasification of POD method is described. Then, applications of POD method in particle image velocimetry (PIV) technology and computational fluid dynamics (CFD) data processing are listed in detail. The advantages and disadvantages of POD method and dynamic mode decomposition (DMD) method in practical engineering application are compared. The results show that DMD method can be used when the ffow field is steady and pulsating, while POD method is more suitable for other time-varying flow fields. Finafly, development of POD method, especiaUy its application in the field of artificial intefligence, is prospected.