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.