In this paper, a methodology to design instrument networks optimally selected for the use of
PCA-based monitoring in process plants is presented. Sensors are placed or signals are selected
to minimize the sum of investment cost and the cost of not detecting a fault. This optimization
problem is solved using Genetic Algorithms (GA). It is shown that for existing sensor networks,
the use of fewer signals than the available ones can be, in some cases, advantageous for
monitoring purposes.
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