• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.1
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• pp.53-58
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• 2005

Water shortages are gradually accelerating because higher standards of living are required and water resources are more heavily utilized. Therefore, effective water treatment is necessary in order to retain the required qualify and amount of water. General treatment includes coagulation, flocculation, filtering, and disinfection. coagulation, flocculation, and disinfection are major components of water treatment processes. In this paper, a new automatic decision algorithm is proposed for coagulation. The proposed method shows how to determine the coagulant type and amount using data mining techniques.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.12 no.3
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• pp.104-113
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• 1998

In genral, the water process facilities include the purification plant, the waste water plant and the process of this purification plant is consisted of the intake, coagulation, settling, filtration, disinfection. The coagulation is very important in filtration processing plant and is very related to process of turbidity. The coagulation to the turbidity is, however, not yet to be clarified and the amount of coagulant can not be easily calculated. Moreover the coagulant dosing amount has to be decided adaptively according to the qualities of the raw water. So, the automation of chemicals dosing process and the supervisory system were needed to improve the performance of facilities. In this paper, a neural network is employed to model the coagulation to the turbidity of the treated water and the historical jar-test data are used to train the neural network. And also, an automation system to support the coagulant dosing process using the neural network was implemented and was shown by the field test. This automation system for the operator support system was constructed the environment to supervise the state an management of facilities for the maintenance.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.10a
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• pp.223-226
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• 2004

본 논문은 정수장에서 사용하는 응집제의 종류와 주입량을 결정하기 위한 시스템 개발에 관한 내용이다. 정수장은 여러 단위 처리장으로 구성되며, 탁도와 색도를 제거하기 위하여 혼화지에서 응집제를 주입하여 침전을 시킨다. 현재까지 응집제 결정을 위해 Jar-test를 이용하였는데, 이 방법은 사람의 주관적인 판단에 의존하므로 실험 오차가 발생할 수 있다. 특히 정수장의 자동화를 위한 시스템 개발에서 가장 큰 걸림돌로 작용하고 있다. 본 논문은 이러한 문제점을 해결하기 위하여 데이터 마이닝 기법 등을 이용한 응집제 종류와 양을 결정하는 제어기를 개발하였다.

• Journal of Korean Society of Environmental Engineers
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• v.39 no.4
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• pp.201-207
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• 2017

This study was conducted to investigate the characteristics of the stream current detector (SCD) and charge analyzing system (CAS), which are well known as the automatic coagulant dosage determination instruments. When the SCD system was used, the current charge value set at pH 9.3 could not be used as the coagulant dosage when the pH of the raw water decreased to 5.7, and the current charge value corresponding to pH 5.7 was required to be reset. In case of CAS system, polydadmac is stable as a cationic titrant when the pH of the raw water ranged 9.3 to 6.0. And it was effective to use polydadmac as a cationic titrant for high turbidity water. The current charge of polydadmac was almost constant between pH 5 and 11, however, the difference in charge of alum is six times in this pH range. Therefore, when the pH of the raw water was changed, it seems that the coagulant used in the actual water treatment plant was as a good cationic titrant.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.7
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• pp.1582-1587
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• 2005

In coagulant control of water treatment plants, rule extraction, one of datamining categories, was performed for coagulant control of a water treatment plant. Clustering methods were applied to extract control rules from data. These control rules can be used for fully automation of water treatment plants instead of operator's knowledge for plant control. To perform fuzzy clustering, there are some coefficients to be determined and these kinds of studies have been performed over decades such as clustering indices. In this study, statistical indices were taken to calculate the number of clusters. Simultaneously, seed points were found out based on hierarchical clustering. These statistical approaches give information about features of clusters, so it can reduce computing cost and increase accuracy of clustering. The proposed algorithm can play an important role in datamining and knowledge discovery.

• Journal of Korean Society of Environmental Engineers
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• v.38 no.9
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• pp.482-496
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• 2016

Algal blooms of cyanobacteria (blue-green Algae) due to the eutrophication of rivers and lakes can cause not only the damage by its biological toxins but also the economic loss in drinking water treatment. The natural algae coagulant, a commercial product known as W.H. containing the algicidal and allelopathic material derived from oak, can control algal problems proactively through the coagulation flotation process. However, because there have been no applications of the process for pre-treatment in drinking water plants, we could find no report on the optimum injection dose of W.H.. In this study, we have conducted several sets of jar-tests while changing W.H. dose and concentration of chl-a for (1) Han-river samples and (2) subcultured cyanobacteria samples, and monitored the removal mechanisms of algae intensively. Based on these jar-test results, two linear equations with variables of chl-a and turbidity have been deduced to predict the optimal W.H. dose after the multiple regression analysis using IBM-SPSS. Also, prototypes of automatic control logic have been suggested to inject the optimal W.H. dose promptly in response to the variation of water quality.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.6
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• pp.792-798
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• 2021

In this paper, an algorithm for determining the coagulant input rate in the drug-injection tank during the process of the water purification plant was derived through big data analysis and prediction based on artificial intelligence. In addition, analysis of big data technology and AI algorithm application methods and existing academic and technical data were reviewed to analyze and review application cases in similar fields. Through this, the goal was to develop an algorithm for determining the coagulant input rate and to present the optimal input rate through autonomous driving simulator and pilot operation of the coagulant input process. Through this study, the coagulant injection rate, which is an output variable, is determined based on various input variables, and it is developed to simulate the relationship pattern between the input variable and the output variable and apply the learned pattern to the decision-making pattern of water plant operating workers.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.7
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• pp.1588-1593
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• 2005

In coagulant control of water treatment plants, rule extraction, one of datamining categories, was performed for coagulant control of a water treatment plant. Clustering methods were applied to extract control rules from data. These control rules can be used for fully automation of water treatment plants instead of operator's knowledge for plant control. To perform fuzzy clustering, there are some coefficients to be determined and these kinds of studies have been performed over decades such as clustering indices. In this study, statistical indices were taken to calculate the number of clusters. Simultaneously, seed points were found out based on hierarchical clustering. These statistical approaches give information about features of clusters, so it can reduce computing cost and increase accuracy of clustering. The proposed algorithm can play an important role in datamining and knowledge discovery.

• Journal of Korean Society of Environmental Engineers
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• v.35 no.12
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• pp.877-882
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• 2013

The application of ultrafiltration (UF) and microfiltration (MF) membranes has been increased for drinking water purification. The advantages of UF/MF membrane process compared to conventional treatment processes are stable operation under varying feed water quality, smaller construction area, and automatic operation. Most membrane treatment plants are designed with polymeric membranes. Recently, some studies suggested that the process of treating surface water with ceramic membranes is competitive to the application of polymeric membranes. Higher water flux, less frequent cleaning, and much longer lifetime are the advantages of ceramic membrane comparing to polymeric membrane. Therefore, this research focused on the application of ceramic MF membrane pilot plant at the slow sand filtration plant. The ceramic membrane pilot plant has three trains that used raw water and sand filtered water as a feed water, respectively. For optimizing the pilot plant process, the coagulation with PACl coagulant was used as a pretreatment of ceramic membrane process. In addition, CEB (Chemical Enhanced Backwash) process using $H_2SO_4$ and NaOCl was used for 1.5 days, respectively. The experimental results showed that applying the optimum coagulant dose before membrane filtration showed enhancing membrane fluxes for both raw water and sand filtered water. Also, when using raw water as a feed of membrane, minimum fouling rate was 2.173 kPa/cycle with 25 mg/L of PACl and when using sand filtered water, the minimum fouling rate was 0.301 kPa/cycle with 5 mg/L of PACl.