A model-based supersaturation estimator (inferential or soft-sensor) for industrial sugar crystallization process

Morales, Humberto; Sciascio, Fernando di; Aguirre-Zapata, Estefania; Amicarelli, Adriana N.

doi:10.1016/j.jprocont.2023.103065

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Cited by 3 publications

References 41 publications

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Influence of dispersion of a new type whole crystals seed on crystallization process and sugar quality

Volodymyrovych Tkachenko,

Volodymyrivna Sheiko,

Mykhailivna Anisimova

et al. 2024

Journal of Crystal Growth

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Influence of dispersion of a new type whole crystals seed on crystallization process and sugar quality

Volodymyrovych Tkachenko,

Volodymyrivna Sheiko,

Mykhailivna Anisimova

et al. 2024

Journal of Crystal Growth

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Influence of Dispersion of a New Type Whole Crystals Seed on Crystallization Process and Sugar Quality

Petrenko,

Tkachenko,

Sheiko

et al. 2024

Preprint

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Soft-sensing modeling of mother liquor concentration in the evaporation process based on reduced robust least-squares support-vector machine

Qian,

Xu,

Yuan

2023

MBE

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<abstract><p>The evaporation process is vital in alumina production, with mother liquor concentration serving as a critical control parameter. To address the challenge of online detection, we propose the introduction of a soft measurement strategy. First, due to the significant fluctuations in the production process variables and inter-variable coupling, comprehensive grey correlation analysis and kernel principal component analysis are employed to reduce the input dimension and computational complexity of the data, enhancing the efficiency of the soft sensing model. The reduced robust least-squares support-vector machine (LSSVM), with its commendable predictive performance, is used for modeling and predicting the principal components. Concurrently, an improved Pattern Search-Differential Evolution (PS-DE) algorithm is proposed for optimizing the pivotal parameters of the LSSVM network. Lastly, on-site industrial data validation indicates that the new model offers superior tracking capabilities and heightened accuracy. It is deemed aptly suitable for the online detection of mother liquor concentration.</p></abstract>

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A model-based supersaturation estimator (inferential or soft-sensor) for industrial sugar crystallization process

Cited by 3 publications

References 41 publications

Influence of dispersion of a new type whole crystals seed on crystallization process and sugar quality

Influence of dispersion of a new type whole crystals seed on crystallization process and sugar quality

Influence of Dispersion of a New Type Whole Crystals Seed on Crystallization Process and Sugar Quality

Soft-sensing modeling of mother liquor concentration in the evaporation process based on reduced robust least-squares support-vector machine

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