Multivariate statistical process monitoring methods such as PCA and ICA are always based on a variety of assumptions. If the constraints of these methods have not been considered when selecting these methods， wrong conclusions will be obtained and the rate of high leaking and false alarm will be increased. To solve the constraints problem of these methods in application， a data characteristic analysis method was proposed to test the correlation of the variables automatically， in which parameter optimization was conducted and the set of linear variables was eliminated sequentially. The simulation illustrated that the proposed method can select appropriate modelling method automatically according to data characteristics and applicable conditions of the methods， which has considerable practical value.
