Virtual sensors allow the measuring of variables for which no physical
sensor is available using indirect measurements of related variables.
In this work we describe the implementation of a virtual sensor for the
zinc coating thickness in a hot dip galvanizing line from related process
variables such as blowing pressure, knives-to-strip distance, knives-topot
distance, etc., based on artificial neural networks that model nonlinear
dynamical relationships. The virtual sensor is currently working on
Avilés Galvanizing 2.