95 research outputs found

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

    Get PDF
    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

    Get PDF
    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

    Get PDF
    Pour avoir un fonctionnement de l'usine sĂ»r et bĂ©nĂ©fique, des donnĂ©es prĂ©cises et fiables sont nĂ©cessaires. D'une maniĂšre gĂ©nĂ©rale, une information prĂ©cise mĂšne Ă  de meilleures dĂ©cisions et, par consĂ©quent, de meilleures actions pour aboutir aux objectifs visĂ©s. Dans un environnement industriel, les donnĂ©es souffrent de nombreux problĂšmes comme les erreurs de mesures (autant alĂ©atoires que systĂ©matiques), l'absence de mesure de variables clĂ©s du procĂ©dĂ©, ainsi que le manque de consistance entre les donnĂ©es et le modĂšle du procĂ©dĂ©. Pour amĂ©liorer la performance de l'usine et maximiser les profits, des donnĂ©es et des informations de qualitĂ© doivent ĂȘtre appliquĂ©es Ă  l'ensemble du contrĂŽle de l'usine, ainsi qu'aux stratĂ©gies de gestion et d'affaires. Comme solution, la rĂ©conciliation de donnĂ©es est une technique de filtrage qui rĂ©duit l'impact des erreurs alĂ©atoires, produit des estimations cohĂ©rentes avec un modĂšle de procĂ©dĂ©, et donne Ă©galement la possibilitĂ© d'estimer les variables non mesurĂ©es. Le but de ce projet de recherche est de traiter des questions liĂ©es au dĂ©veloppement, la mise en Ɠuvre et l'application des observateurs de rĂ©conciliation de donnĂ©es pour les industries minĂ©ralurgiques et mĂ©tallurgiques. Cette thĂšse explique d’abord l'importance de rĂ©gler correctement les propriĂ©tĂ©s statistiques des incertitudes de modĂ©lisation et de mesure pour la rĂ©conciliation en rĂ©gime permanent des donnĂ©es d’usine. Ensuite, elle illustre la façon dont les logiciels commerciaux de rĂ©conciliation de donnĂ©es Ă  l'Ă©tat statique peuvent ĂȘtre adaptĂ©s pour faire face Ă  la dynamique des procĂ©dĂ©s. La thĂšse propose aussi un nouvel observateur de rĂ©conciliation dynamique de donnĂ©es basĂ© sur un sous-modĂšle de conservation de la masse impliquant la fonction d'autocovariance des dĂ©fauts d’équilibrage aux nƓuds du graphe de l’usine. Pour permettre la mise en Ɠuvre d’un filtre de Kalman pour la rĂ©conciliation de donnĂ©es dynamiques, ce travail propose une procĂ©dure pour obtenir un modĂšle causal simple pour un circuit de flottation. Un simulateur dynamique basĂ© sur le bilan de masse du circuit de flottation est dĂ©veloppĂ© pour tester des observateurs de rĂ©conciliation de donnĂ©es et des stratĂ©gies de contrĂŽle automatique. La derniĂšre partie de la thĂšse Ă©value la valeur Ă©conomique des outils de rĂ©conciliation de donnĂ©es pour deux applications spĂ©cifiques: une d'optimisation en temps rĂ©el et l’autre de commande automatique, couplĂ©es avec la rĂ©conciliation de donnĂ©es. En rĂ©sumĂ©, cette recherche rĂ©vĂšle que les observateurs de rĂ©conciliation de donnĂ©es, avec des modĂšles de procĂ©dĂ© appropriĂ©s et des matrices d'incertitude correctement rĂ©glĂ©es, peuvent amĂ©liorer la performance de l'usine en boucle ouverte et en boucle fermĂ©e par l'estimation des variables mesurĂ©es et non mesurĂ©es, en attĂ©nuant les variations des variables de sortie et des variables manipulĂ©es, et par consĂ©quent, en augmentant la rentabilitĂ© 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

    Get PDF
    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

    Bubble Size in a Cocurrent Fiber Slurry

    Full text link

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

    Get PDF
    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

    Get PDF
    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

    Get PDF
    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

    Get PDF
    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

    Get PDF
    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
    • 

    corecore