Multivariate Statistical Process Control and Case-Based Reasoning for situation assessment of Sequencing Batch Reactors

Abstract

ABSRACT This thesis focuses on the monitoring, fault detection and diagnosis of Wastewater Treatment Plants (WWTP), which are important fields of research for a wide range of engineering disciplines. The main objective is to evaluate and apply a novel artificial intelligent methodology based on situation assessment for monitoring and diagnosis of Sequencing Batch Reactor (SBR) operation. To this end, Multivariate Statistical Process Control (MSPC) in combination with Case-Based Reasoning (CBR) methodology was developed, which was evaluated on three different SBR (pilot and lab-scales) plants and validated on BSM1 plant layout.

EN Esta tesis se enfoca en la monitorización, detección de defectos y diagnosis de Plantas de Tratamiento de Aguas Residuales (Wastewater Treatment Plants - WWTP), el cual son importantes campos de investigación par un amplio rango de disciplinas en Ingeniería. El objetivo principal es evaluar y aplicar una metodología novel de inteligencia artificial basada en evaluación, monitorización y diagnosis de la operación de Reactores de secuencia por lotes (Sequencing Batch Reactor -SBR). Para lograr este fin, se desarrolla una metodología que combina Control de Procesos Multivariable (Multivariate Statistical Process Control -MSPC) con Razonamiento Basado en Casos (Case-Based Reasoning -CBR)., el cual se evalúa en tres diferentes plantas SBR y se valida en una planta BSM1.