A recursive multi-block PLS algorithm for monitoring industrial processes

Abstract

Industrial processes often present a large number of highly correlated variables that are frequently measured and consist of several operating units. For monitoring such processes multi-block partial least squares (MBPLS) has shown to be capable of dividing the variables according to operating units and can reduce the number variables that describe significant process variation with sufficient accuracy. As shown in this paper, MBPLS may run into difficulties when the process exhibits nonstationary behaviour. To overcome this deficiency, the development of recursive MBPLS is discussed including an application study that relates to a realistic simulation of a fluid catalytic cracking unit.