Multivariate Projection Methods Applied To The Contact Section Of A Sulphuric Acid Plant

On line monitoring and diagnosis systems of process operating performance are becoming an important part of industrial programs, leading to improve process operation and therefore product quality over time. In processes, such as the contact section of a sulphuric acid plant, a large number of input variables, highly correlated, are presented. These characteristics usually pose more difficulties in modelling the process for monitoring and diagnosis purposes. Multivariate statistical projection methods, such as Main Component Analysis, have been proposed to effectively deal with these situations. The application of these ideas to a section of a 2350 MTD sulphuric acid plant, located at the Caletones Smelter, including dry tower, gas blowers, catalytic reactor and S03 absorber processes, is discussed here. A PCA model with eight main components is used for monitoring and diagnosis of more than seventy operating variables. Hottelling's T2 and Q residuals test were used for detecting measurement problems in relevant variables, and for identifying which set of variables were responsible for driving the process outside its normal operating region. Furthermore, considerable information for the correction of the tested operating problems was given by the use of these techniques.