VISUALIZATION OF MULTIVARIATE PROCESSES USING PRINCIPAL COMPONENT ANALYSIS AND NONLINEAR INVERSE MODELING

Interpretation of the state of industrial processes is considered usin g principal component analysis as a visualization technique. A procedu re for using the resulting two dimensional maps in detecting upsets an d faults of the process is described. Nonlinear inverse models from th e map coordinates back to the original process variables are studied a nd compared to linear modelling methods. Visualization techniques toge ther with inverse modelling methods are shown to form a useful decisio n support system for the operating personnel of the plant. The visuali zation techniques and inverse modelling are studied using a simulated chemical process as an example.