Método para la estimación de estado en procesos de molienda de minerales con molino semiautógeno
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Autores
Cortés Calle, Carlos César
Director
Botero Castro, Héctor Antonio
Tipo de contenido
Trabajo de grado - Maestría
Idioma del documento
EspañolFecha de publicación
2022
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Resumen
La implementación de controladores avanzados en procesos de molienda de minerales que permitan la optimización, por ejemplo la minimización en el consumo de agua, requiere la medición completa del estado. Sin embargo, esto es en muchos casos imposible debido a la no disponibilidad de sensores para ello. Por lo tanto, en este trabajo se diseñó un estimador de estado tipo filtro de Kalman, para el proceso de molienda de minerales conocido como molino semiautógeno (SAG). Para lograr lo anterior, se obtuvo un modelo semifísico de base fenomenológica del proceso de molienda, se probó la observabilidad no lineal del mismo, se discretizó el modelo, se diseñó el estimador de estado tipo filtro de Kalman extendido, se simuló su comportamiento ante perturbaciones y se verificó el correcto funcionamiento del estimador. Finalmente, se explicaron las condiciones necesarias para la implementación real del estimador y se presentaron esquemas para mejorar el desempeño en una planta industrial. (Texto tomado de la fuente)
Implementing advanced controllers in mineral grinding processes that optimize the process, such as minimizing water consumption, requires the complete measurement of the states. However, it is impossible in many cases due to the unavailability of sensors.Therefore, in this work, a Kalman filter state estimator was designed for the grindingprocess known as a semi-autogenous mill (SAG). Thus, a phenomenologically basedsemi-physical grinding mill model was obtained, the nonlinear observability was tested, the model was discretized, the extended Kalman filter was designed, its behaviorunder disturbances was simulated, and the correct performance of the estimator wasverified. Finally, the necessary conditions for implementing the estimator were explained, and schemes to improve performance in an industrial plant were presented.
Implementing advanced controllers in mineral grinding processes that optimize the process, such as minimizing water consumption, requires the complete measurement of the states. However, it is impossible in many cases due to the unavailability of sensors.Therefore, in this work, a Kalman filter state estimator was designed for the grindingprocess known as a semi-autogenous mill (SAG). Thus, a phenomenologically basedsemi-physical grinding mill model was obtained, the nonlinear observability was tested, the model was discretized, the extended Kalman filter was designed, its behaviorunder disturbances was simulated, and the correct performance of the estimator wasverified. Finally, the necessary conditions for implementing the estimator were explained, and schemes to improve performance in an industrial plant were presented.
Abstract
Descripción Física/Lógica/Digital
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