Fuzzy control of coagulation reaction through streaming current monitoring

Liu, J. C.; Wu, M. D.

doi:10.2166/wst.1997.0102

Cited by 5 publications

(3 citation statements)

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“…Liu and Wu [96] conducted jar tests and continuous bench-scale experiments with synthetic raw water and ferric chloride as coagulant. They applied a fuzzy logic feed-backward control system with streaming current (set point −0.05) and pH (set point 8.0) as input, and coagulant dose as well as base dose as output parameters.…”

Section: Fuzzy Logic Modelsmentioning

confidence: 99%

State of the Art of Online Monitoring and Control of the Coagulation Process

Ratnaweera

Fettig

2015

Water

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Abstract:Coagulation is an essential process for the removal of suspended and colloidal material from water and wastewater. However, no comprehensive or universally accepted mathematical description of the process has been developed so far. Therefore, process optimization and control is usually based on data from jar tests and simple flow-proportional dosing concepts, while more accurate concepts based on water quality parameters that can be measured online are emerging. In addition, there have been attempts to develop software sensors and control schemes that involve advanced mathematical analyses of these parameters. The paper presents an overview of the parameters and physical sensors that are used for feed-forward and feed-backward control schemes and the experiences that have been made with their implementation. Moreover, the development and use of software sensors is described. Finally, the practical applications of different control techniques are given in order to illustrate the state of the art of coagulation control. Some thoughts about research needs conclude this review.

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Section: Fuzzy Logic Modelsmentioning

confidence: 99%

State of the Art of Online Monitoring and Control of the Coagulation Process

Ratnaweera

Fettig

2015

Water

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“…Ainsi, d'importants efforts et différentes approches ont été développés pour construire et mettre en oeuvre des modèles de contrôle automatique de la dose de coagulant (BAZER-BACHI et al, 1986;EVANS et ENOCH, 1998;GAGNON et al, 1997;VALENTIN et al, 1999) et des outils de supervision permettant d'optimiser ce procédé de traitement (KAN et HUANG, 1998;LIU et WU, 1997;STANDEN et al, 1997). En ce qui concerne les outils dits de supervision, dans le cas des travaux de KAN et HUANG (1998), même si on parle de supervision ou de suivi, l'essentiel du développement porte sur la détermination automatique de la dose de coagulant grâce à un suivi optique.…”

Section: Introductionunclassified

Gestion supervisée d’une unité de coagulation pour la potabilisation des eaux à partir d’une méthodologie d’apprentissage et d’expertise

Lamrini¹,

Lann

Lakhal³

et al. 2008

rseau

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Résumé Le travail présenté propose une méthodologie de classification par apprentissage qui permet l’identification des états fonctionnels sur une unité de coagulation impliquée dans le traitement des eaux de surface. La supervision et le diagnostic de ce procédé ont été réalisés en utilisant la méthode de classification LAMDA (Learning Algorithm for Multivariate Data Analysis). Cette méthodologie d’apprentissage et d’expertise permet d’exploiter et d’agréger toutes les informations provenant du procédé et de son environnement ainsi que les connaissances de l’expert. L’étude montre qu’il est possible d’ajouter aux informations issues des capteurs classiques (température, matières en suspension, pH, conductivité, oxygène dissous), la valeur de la dose de coagulant calculée par un capteur logiciel développé dans une étude antérieure afin d’affiner le diagnostic. Le site d’application choisi pour l’identification des états fonctionnels est la station de production d’eau potable Rocade de la ville de Marrakech, Maroc.

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“…Correlations between streaming current and electrophoretic mobility measurements have shown that the two parameters are linearly related (Liu & Wu, 1997; Dentel et al, 1989). However, an offset exists between streaming current and electrophoretic mobility measurements in such a manner that an electrophoretic mobility value of zero corresponds to a negative streaming current value.…”

Section: Introductionmentioning

confidence: 99%

Optimizing ferric sulfate coagulation of algae with streaming current measurements

Briley¹,

Knappe²

2002

Journal AWWA

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This study sought to determine ferric sulfate coagulation conditions that lead to effective removal of algae by conventional gravity sedimentation. Using laboratory‐cultured Anabaena flos‐aquae spiked into natural water, charge titrations and jar tests were conducted to evaluate the effects of streaming current value, coagulation pH, and initial algae concentration on the removal of algae, turbidity, and natural organic matter. At pH 6, ferric sulfate doses corresponding to the point of zero charge (PZC), as determined by streaming current measurements, consistently produced low settled water algae concentrations when an anionic flocculant aid was added. In contrast, ferric sulfate coagulation at pH 7.0 and 7.5 was not effective for algae removal because the algae's surface charge could not be sufficiently neutralized. At pH 6 and the PZC, settled water algae concentrations, turbidity, and ultraviolet absorbance at 254 nm were similar for tests conducted at initial algae concentrations of 10,000 and 50,000 cells/mL, but a larger coagulant dose was required to reach the PZC at the higher initial algae concentration. Thus, adjusting coagulant doses based on streaming current value should be effective for maintaining settled water quality in plants that treat waters with rapidly varying influent algae concentrations and/or background water quality. Experiments conducted with a natural algae bloom sample confirmed that ferric sulfate coagulation at pH 6 and the PZC was effective for algae removal.

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Fuzzy control of coagulation reaction through streaming current monitoring

Cited by 5 publications

References 0 publications

State of the Art of Online Monitoring and Control of the Coagulation Process

State of the Art of Online Monitoring and Control of the Coagulation Process

Gestion supervisée d’une unité de coagulation pour la potabilisation des eaux à partir d’une méthodologie d’apprentissage et d’expertise

Optimizing ferric sulfate coagulation of algae with streaming current measurements

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