Application of Radial Basis Functions — Partial Least Squares to non-linear pattern recognition problems: diagnosis of process faults

Performance and robustness of a newly proposed approach (based on the Radial Basis Function and PLS2) in the non-linear pattern recognition problem is studied and compared with those of Radial Basis Function Network (RBFN) and multilayer feed-forward network (MLP). An example concerns classification of process faults. The presented results show that the RBF-PLS2 method can be treated as an alternative for the RBFN and MLP approaches, with an additional advantage over MLP as a linear method.