Phenomenological Based Soft Sensor for Online Estimation of Slurry Rheological Properties

Jenny L. Diaz C, Diego A. Muñoz, Hernan Alvarez

    Producción científica: Contribución a una revistaArtículo en revista científica indexadarevisión exhaustiva

    2 Citas (Scopus)


    This work proposes a soft sensor based on a phenomenological model for online estimation of the density and viscosity of a slurry flowing through a pipe-and-fittings assembly (PFA). The model is developed considering the conservation principle applied to mass and momentum transfer and considering frictional energy losses to include the variables directly affecting slurry properties. A reported proposal for state observers with unknown inputs is used to develop the first block of the observer structure. The second block is constructed with two options for evaluating slurry viscosity, generating two possible estimator structures, which are tested using real data. A comparison between them indicates different uses and capabilities according to available process information.

    Idioma originalInglés
    Páginas (desde-hasta)696-706
    Número de páginas11
    PublicaciónInternational Journal of Automation and Computing
    EstadoPublicada - 1 oct. 2019

    Nota bibliográfica

    Publisher Copyright:
    © 2018, Institute of Automation, Chinese Academy of Sciences and Springer-Verlag GmbH Germany, part of Springer Nature.


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