Soft sensor design for power measurement and diagnosis in electrical furnace: A parametric estimation approach

Abstract : In this paper, we propose as a first step a software solution to measure the electrical power consumed in an industrial furnace intended essentially for heat treatments. The soft sensor is constructed from the power physical measurement taken as the output of the set (dimmer + resistances), and the control signal measurement provided by a controller with an unknown structure. The second step consists in a detection of faults like a resistance disconnection, for instance. This phase requires the knowledge of the controller model and the furnace system. An overparametrization method was chosen for the controller estimation. An indirect closed-loop Input-Output (IO) identification approach was used for the furnace model estimation through a Tailor-Made and a decomposition of the closed-loop algorithms. A validation with two other experimental tests concludes the paper.
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Baya Hadid, Erik Etien, Régis Ouvrard, Thierry Poinot, Laurent Le Brusquet, et al.. Soft sensor design for power measurement and diagnosis in electrical furnace: A parametric estimation approach. IECON 2013, Nov 2013, Vienne, Austria. pp.2191 - 2196, ⟨10.1109/IECON.2013.6699471⟩. ⟨hal-00932274⟩

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