Abstract
Multivariate Statistical Process Control (MSPC) techniques require process stationarity as a main rule for design and monitoring. However, a critical process such as Boiler and Turbine-Generator units of Thermoelectric Power Plants, which is a multivariable complex system, features different types of non-stationary behavior and operational modes with constant changes of set points of key performance variables. A methodology based on MSPC and Principal Component Analysis (PCA) is presented with an adaptive mean estimator that deals with frequent changes of set points, both for design and just in time monitoring. Experimental results, based on data from a power plant, illustrate the application and use of the methodology.
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