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Neyman–Pearson Test for Fault Detection in the Process Dynamics

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Abstract

Fault detection in industrial plants plays an important role for ensuring the product quality, safety, and reliability of plant equipment. The purpose of this work is to propose a fault detection technique with a black-box modeling and a statistical module based on Neyman–Pearson test (NPT). In fact, Nonlinear Auto-Regressive Moving Average with eXogenous input (NARMAX) model is used to obtain a model for the normal condition operation. To detect a fault, The NPT has been applied to the residual of NARMAX model. The efficiency of the technique is illustrated through its application to monitor product quality in a distillation unit.

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Authors and Affiliations

  1. Automatic Laboratory of Setif, Department of Electrical Engineering, Setif 1 University, Setif, Cité Maabouda, Route de Béjaia, 19000, Sétif, Algeria

    Lakhdar Aggoune

  2. Chemical Engineering Department, Université de Rouen, IUT, Rue Lavoisier, 76130, Mont-Saint-Aignan, France

    Yahya Chetouani

  3. IRSEEM, ESIGELEC, Technopôle du Madrillet, Avenue Galilée, 76800, Saint-Étienne-du-Rouvray, France

    Yahya Chetouani

Authors
  1. Lakhdar Aggoune
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  2. Yahya Chetouani
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Correspondence to Lakhdar Aggoune.

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Aggoune, L., Chetouani, Y. Neyman–Pearson Test for Fault Detection in the Process Dynamics. J Fail. Anal. and Preven. 16, 999–1005 (2016). https://doi.org/10.1007/s11668-016-0186-y

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  • DOI: https://doi.org/10.1007/s11668-016-0186-y

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