The aim is to study a continuous chemical process, and then analyze the hold process of the reactor and build the models which could be trained to realize the fault diagnosis and localization in the process. An experimental system has been built to be the research base. That includes experiment part and record system. To the diagnosis and localization methods, the work presented the methods with the data-based approach, mainly the Bayesian network and RBF network based on GAAPA (Genetic Algorithm with Auto-adapted of Partial Adjustment). The data collected from the experimental system are used to train and test the models.

Significant advances have been made in the understanding of living/controlled radical polymerization processes since their discovery in the early 1990’s. These processes enable an unprecedented degree of control over polymer architecture that was previously not possible using conventional radical polymerization processes, and this has made possible the synthesis of many new and interesting materials. However, there has been only limited success in commercializing these new methods. Recently there has been increased focus on the development of more industrially viable processes. Dispersed aqueous phase reactions have received much attention because these water-based processes have several technical, economic, and environmental benefits over the more common solution and bulk reactions that were originally developed. Likewise, there has been some investigation of using continuous reactors that have potential technical and economic benefits over the more commonly employed batch reactors. This thesis presents an in-depth study that combines the three aforementioned technologies: living/controlled radical polymerization, dispersed phase aqueous reactions, and continuous reactors. Specifically, the system of interest is a nitroxide-mediated miniemulsion polymerization reaction in a continuous tubular reactor to produce polymer latex. Design of the continuous tubular reactor is discussed in some detail with a focus on specific technical challenges that were faced in building a functional apparatus for this system. Scoping experiments are described which identified a significant effect of temperature ramping rate that is critical to understand when moving to larger scale reactors for this system. The unexpected phenomenon of room temperature polymerization initiated by ascorbic acid is also described. There is demonstration for the first time that bulk and miniemulsion polymers can be produced in a tubular reactor under controlled nitroxide-mediated polymerization conditions, and copolymers can be produced. A detailed residence time distribution study for the tubular reactor is also shown, and several interesting phenomena are discussed that have implications on the practical operating conditions of the tubular reactor. This particular study makes it clear that one should experimentally verify the residence time distribution within a continuous system with the reactants of interest, and that model systems may not give an accurate picture of the real system. / Thesis (Ph.D, Chemical Engineering) -- Queen's University, 2010-12-20 12:00:37.974

Ce travail concerne l’étude d’un réacteur chimique continu afin de construire un modèle pour la phase d’apprentissage de méthode et localisation et détection de pannes. Un dispositif expérimental a été conçu pour disposer de données expérimentales significatives. Pour le diagnostique et la localisation des méthodes orientées données ont été retenues, principalement les réseaux Bayésiens et les réseaux de neurones à Fonctions Radiales de Base (RBF) couplés à un algorithme génétique auto adaptatif à ajustement local (GAAPA). Les données collectées à partir du dispositif expérimental ont servi à l’apprentissage et à la validation du modèle. / The aim is to study a continuous chemical process, and then analyze the hold process of the reactor and build the models which could be trained to realize the fault diagnosis and localization in the process. An experimental system has been built to be the research base. That includes experiment part and record system. To the diagnosis and localization methods, the work presented the methods with the data-based approach, mainly the Bayesian network and RBF network based on GAAPA (Genetic Algorithm with Auto-adapted of Partial Adjustment). The data collected from the experimental system are used to train and test the models.