Fault Detectability Index for Optimal Monitoring System Design

D. ZUMOFFEN; L. NIETO; M. BASUALDO

PEM Fuel Cells with Bio-Ethanol Processor Systems: A Multidisciplinary Study of Modelling, Simulation, Fault Diagnosis and Advanced Control

SPRINGER

Año: 2010;

In this chapter an approach based on fault detectability study for deciding the optimal measurements selection to build the principal component analysis (PCA) model using combined statistics is addressed. It is thought for improving the monitoring systems design (MSD). The methodology applied here to the bioethanol processor with PEMFC is done integrated to the previous stage of optimal sensor network and control structure selection detailed in Chapter 12. The problem dimensionality could be important so genetic algorithms (GA) for stochastic global search is preferred to solve it. The solution can be driven properly to avoid the inclusion of other sensors than those installed for control purposes. It can be done through a good definition of the functional cost. The capacity of this methodology is demonstrated with a set of typical and critical faults that could occur to this complex process.