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Data Reconciliation and Gross Error Detection in Industrial Processes: State of the Art and Focus on Heat Transfer
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  • Jose Loyola-Fuentes,
  • Emilio Diaz-Bejarano,
  • Carlos Planelles,
  • Francesco Coletti
Jose Loyola-Fuentes
Hexxcell Ltd.
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Emilio Diaz-Bejarano
Hexxcell Ltd.
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Carlos Planelles
Hexxcell Ltd.
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Francesco Coletti
Hexxcell Ltd.

Corresponding Author:[email protected]

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Abstract

In a variety of systems, heat transfer is crucial for the optimal use of energy. The correct interpretation of heat transfer data is driven heavily by data pre-processing. Examples are Data Reconciliation (DR) and Gross Error Detection (GED). These techniques are suitable when a process model is available. This is advantageous compared to statistical methods, since the physical relationships among measured variables are considered. This make the use of DR and GED in heat transfer applications convenient, as conservation laws are usually well derived. This work aims to review the most common methods for DR and GED, in the context of heat transfer equipment. Preliminary concepts for these techniques are provided. Then, each method is described with their advantages and disadvantages. Next, the focus is turned into heat transfer applications. Finally, guidelines are proposed to guide the selection of suitable DR and GED strategies in future heat transfer studies.