Probability density function of bubble size based reagent dosage predictive control for copper roughing flotation

As an effective measurement indicator of bubble stability, bubble size structure is believed to be closely related to flotation performance in copper roughing flotation. Moreover, reagent dosage has a very important influence on bubble size structure. In this paper, a novel reagent dosage predictive control method based on probability density function (PDF) of bubble size is proposed to implement the indices of roughing circuit. Firstly, the froth images captured in the copper roughing are segmented by using a two-pass watershed algorithm. In order to characterize bubble size structure with non-Gaussian feature, an entropy based B-spline estimator is hence investigated to depict the PDF of the bubble size. Since the weights of B-spline are interrelated and related to the reagent dosage, a multi-output least square support vector machine (MLS-SVM) is applied to depict a dynamic relationship between the weights and the reagent dosage. Finally, an entropy based optimization algorithm is proposed to determine reagent dosage in order to implement tracking control for the PDF of the output bubble size. Experimental results can show the effectiveness of the proposed method

Bubble Size in a Cocurrent Fiber Slurry

Bubble diameter measurements in a two-dimensional cocurrent bubble column are obtained using a gas−liquid−solid system in which the solid component is a cellulose fiber. Flash X-ray radiography, a noninvasive measurement technique, is used to record bubble size in the opaque slurry at various operating conditions. Results are presented for a range of fiber mass fractions (0 ≤ C ≤ 1.5%), a range of superficial gas velocities (1 ≤ υg ≤ 4 cm/s), two superficial liquid velocities (υl = 1 or 2 cm/s), and two column heights (H = 15−40 or 115−140 cm). Bubbles are categorized as either large (dB \u3e 10 mm) or small (dB ≤ 10 mm), and all bubble diameter distributions can be characterized by log-normal distributions. The presence of fibers has the most significant effect on the large bubble size and population, even at mass fractions as low as 0.5%. In general, the large bubble size and population increases with column height, superficial gas velocity, and fiber mass fraction

Data reconciliation for mineral and metallurgical processes : Contributions to uncertainty tuning and dynamic balancing : Application to control and optimization

Pour avoir un fonctionnement de l'usine sûr et bénéfique, des données précises et fiables sont nécessaires. D'une manière générale, une information précise mène à de meilleures décisions et, par conséquent, de meilleures actions pour aboutir aux objectifs visés. Dans un environnement industriel, les données souffrent de nombreux problèmes comme les erreurs de mesures (autant aléatoires que systématiques), l'absence de mesure de variables clés du procédé, ainsi que le manque de consistance entre les données et le modèle du procédé. Pour améliorer la performance de l'usine et maximiser les profits, des données et des informations de qualité doivent être appliquées à l'ensemble du contrôle de l'usine, ainsi qu'aux stratégies de gestion et d'affaires. Comme solution, la réconciliation de données est une technique de filtrage qui réduit l'impact des erreurs aléatoires, produit des estimations cohérentes avec un modèle de procédé, et donne également la possibilité d'estimer les variables non mesurées. Le but de ce projet de recherche est de traiter des questions liées au développement, la mise en œuvre et l'application des observateurs de réconciliation de données pour les industries minéralurgiques et métallurgiques. Cette thèse explique d’abord l'importance de régler correctement les propriétés statistiques des incertitudes de modélisation et de mesure pour la réconciliation en régime permanent des données d’usine. Ensuite, elle illustre la façon dont les logiciels commerciaux de réconciliation de données à l'état statique peuvent être adaptés pour faire face à la dynamique des procédés. La thèse propose aussi un nouvel observateur de réconciliation dynamique de données basé sur un sous-modèle de conservation de la masse impliquant la fonction d'autocovariance des défauts d’équilibrage aux nœuds du graphe de l’usine. Pour permettre la mise en œuvre d’un filtre de Kalman pour la réconciliation de données dynamiques, ce travail propose une procédure pour obtenir un modèle causal simple pour un circuit de flottation. Un simulateur dynamique basé sur le bilan de masse du circuit de flottation est développé pour tester des observateurs de réconciliation de données et des stratégies de contrôle automatique. La dernière partie de la thèse évalue la valeur économique des outils de réconciliation de données pour deux applications spécifiques: une d'optimisation en temps réel et l’autre de commande automatique, couplées avec la réconciliation de données. En résumé, cette recherche révèle que les observateurs de réconciliation de données, avec des modèles de procédé appropriés et des matrices d'incertitude correctement réglées, peuvent améliorer la performance de l'usine en boucle ouverte et en boucle fermée par l'estimation des variables mesurées et non mesurées, en atténuant les variations des variables de sortie et des variables manipulées, et par conséquent, en augmentant la rentabilité de l'usine.To have a beneficial and safe plant operation, accurate and reliable plant data is needed. In a general sense, accurate information leads to better decisions and consequently better actions to achieve the planned objectives. In an industrial environment, data suffers from numerous problems like measurement errors (either random or systematic), unmeasured key process variables, and inconsistency between data and process model. To improve the plant performance and maximize profits, high-quality data must be applied to the plant-wide control, management and business strategies. As a solution, data reconciliation is a filtering technique that reduces impacts of random errors, produces estimates coherent with a process model, and also gives the possibility to estimate unmeasured variables. The aim of this research project is to deal with issues related to development, implementation, and application of data reconciliation observers for the mineral and metallurgical industries. Therefore, the thesis first presents how much it is important to correctly tune the statistical properties of the model and measurement uncertainties for steady-state data reconciliation. Then, it illustrates how steady-state data reconciliation commercial software packages can be used to deal with process dynamics. Afterward, it proposes a new dynamic data reconciliation observer based on a mass conservation sub-model involving a node imbalance autocovariance function. To support the implementation of Kalman filter for dynamic data reconciliation, a procedure to obtain a simple causal model for a flotation circuit is also proposed. Then a mass balance based dynamic simulator of froth flotation circuit is presented for designing and testing data reconciliation observers and process control schemes. As the last part of the thesis, to show the economic value of data reconciliation, two advanced process control and real-time optimization schemes are developed and coupled with data reconciliation. In summary, the study reveals that data reconciliation observers with appropriate process models and correctly tuned uncertainty matrices can improve the open and closed loop performance of the plant by estimating the measured and unmeasured process variables, increasing data and model coherency, attenuating the variations in the output and manipulated variables, and consequently increasing the plant profitability

A dynamic flotation model for real-time control and optimisation

Thesis (PhD (Electronic Engineering))--University of Pretoria, 2023.Froth flotation models that are developed for circuit design applications are often not suitable for model-based dynamic control and optimisation applications. For real-time control and optimisation applications dynamic models of the key flotation mechanisms are required, as these use real-time measurements to update internal model states and estimate model parameters in real-time. The development of a dynamic froth flotation model is described, based on a combination of fundamental mass and volume balances, fundamental steady-state froth models and empirical models for bubble size and air recovery. The model outputs are defined to correspond with real-time measurements that are commonly available on industrial flotation circuits, including measurements from froth imaging devices in combination with measurements of levels, flow rates, densities and grades. The flotation model is analysed for state observability and controllability, and it is shown that the model states and parameters can be estimated from real-time process measurements that are commonly available on industrial flotation circuits. The ability to estimate process parameters in real-time opens up opportunities for improved process control and optimisation by compensating for a specific flotation mechanism rather than the combined effect of multiple flotation mechanisms. The speed of response can also be improved when more accurate models are maintained by continuously updating model parameters. The flotation model, a state and a parameter estimator and model predictive controller are combined to simulate the potential benefits of using a non-linear model-based approach with state and parameter estimation capabilities in a dynamic control and optimisation application on flotation circuits. The strategy is shown to reject typical process disturbances effectively in the presence of process noise and outperforms a linear non-model based control strategy by a significant margin.Electrical, Electronic and Computer EngineeringPhD (Electronic Engineering)Unrestricte

An analysis of ebullition dynamics in agricultural reservoirs using novel automated sensors

Freshwater systems are an important component of biogeochemical processing within terrestrial landscapes. Only recently has the importance of these systems for contributions to atmospheric budgets of methane (CH4), carbon dioxide (CO2) and nitrous oxide (N2O) been recognized at large spatial scales; however, fluxes of the gases remain poorly described. Smaller aquatic systems (≤ 1 ha) may have a greater role in global carbon (C) cycling than their larger counterparts, partly due to the large collective area of small water bodies. Constructed reservoirs — like the headwater reservoirs in South Tobacco Creek Watershed (STCW), Manitoba, investigated herein — are of particular interest as they, among other benefits, trap nutrients and terrestrial C. Trapped materials in these shallow lentic water bodies are subject to enhanced biogeochemical processing and can be released as greenhouse gases (GHG), including CH4 dominated bubble release from sediments (ebullition). Measurement of ebullition using traditional and novel techniques demonstrated that these reservoirs are hotspots of CH4 generation and release. Across eight reservoirs the mean littoral ebullitive CH4 flux was 2.6 (0.1–6.9) mmol m–2 d–1 during the open-water period of 2017 and was stimulated by autochthonous C fixation — showing the strongest relationships with total ammonia nitrogen and chlorophyll a. This highlights the importance of nutrient export to, and eutrophication within, these systems for stimulating methanogenesis. Mean littoral ebullitive CH4 flux increased significantly during the 2018 open-water season to 12.7 (0.6–40.5) mmol m–2 d–1, and these interannual variations were linked to warmer water temperatures, a result of year to year differences in local hydroclimate. Ebullitive fluxes of CH4 from these reservoirs are higher than reported for most other lentic freshwater systems globally, but interestingly the rates varied strongly both across and within reservoirs. The use of novel sensors allowed ebullition rates in deeper zones to be quantified, and these measurements demonstrated that pelagic fluxes were significantly higher than those from littoral zones — an artifact of reservoir morphology. High temporal resolution records from the sensors also permitted detection of diel variations of ebullitive flux, and was significantly synchronous with sediment temperature at that timescale. This work advances our ability to quantify ebullition fluxes through the use of new sensors by allowing more comprehensive investigations of fluxes than previously possible, and also provides a foundation for agricultural reservoir siting and management strategies to minimize trade-offs associated with CH4 emissions while continuing to confer benefits in terms of nutrient retention and flood control

Advances in Condition Monitoring, Optimization and Control for Complex Industrial Processes

The book documents 25 papers collected from the Special Issue “Advances in Condition Monitoring, Optimization and Control for Complex Industrial Processes”, highlighting recent research trends in complex industrial processes. The book aims to stimulate the research field and be of benefit to readers from both academic institutes and industrial sectors

Future Trends in Advanced Materials and Processes

The Special Issue “Future Trends in Advanced Materials and Processes” contains original high-quality research papers and comprehensive reviews addressing the relevant state-of-the-art topics in the area of materials focusing on relevant or innovative applications such as radiological hazard evaluations of non-metallic materials, composite materials' characterization, geopolymers, metallic biomaterials, etc

Foam fractionation :an effective technology for harvesting microalgae biomass

PhD ThesisHarvesting and dewatering can account for up to 30% of the overall cost of production of usable microalgae biomass for the biotechnology and bioenergy sectors. Harvesting is particularly challenging due to the small amount of algal biomass produced relative to water volume. This process exacts high energy and cost demands and therefore limits further expansion in the microalgae biomass industry. Foam fractionation has potential to deliver a low cost, low energy harvesting solution. Microalgae cells adsorb to the surface of a stream of fine air bubbles, which then rise up a closed column, discharging the concentrated product at the top. Foam fractionation significantly reduces construction, maintenance, and energy costs compared to other harvesting technologies. In this research, a fractional factorial design of experiments followed by a central composite design were used to determine the optimal levels of major variables influencing the harvest of the freshwater microalga Chlorella sp. The effects of bubble size within the liquid pool and foam phase of the harvesting unit were determined, a high concentration factor of 427 as achieved using fluidic oscillation for microbubble generation. The influence of microalgal growth phase on harvest efficiency was investigated to gain insight into the optimal time to harvest during cell cultivation. The effect of surfactant, used to induce foaming, on lipid recovery was examined through methods including total lipid recovery, gas chromatography, energy dispersive x-ray spectrometry and solid phase extraction. The results indicate that the surfactant had the additional benefit of significantly increasing the overall lipid recovery. These encouraging results suggest foam fractionation offers considerable potential as an efficient, low cost, and scalable microalgae biomass harvesting technology

Technology 2004, Vol. 2

Proceedings from symposia of the Technology 2004 Conference, November 8-10, 1994, Washington, DC. Volume 2 features papers on computers and software, virtual reality simulation, environmental technology, video and imaging, medical technology and life sciences, robotics and artificial intelligence, and electronics