• 상하수도학회지
• /
• 제21권5호
• /
• pp.601-607
• /
• 2007

In order to maintain constant residual chlorine in sedimentation basin, It is necessary to develop real time prediction model of residual chlorine considering water treatment plant data such as water qualities, weather, and plant operation conditions. Based on the operation data acquired from K water treatment plant, prediction models of residual chlorine in sediment basin were accomplished. The input parameters applied in the models were water temperature, turbidity, pH, conductivity, flow rate, alkalinity and pre-chlorination dosage. The multiple regression models were established with linear and non-linear model with 5,448 data set. The corelation coefficient (R) for the linear and non-linear model were 0.39 and 0.374, respectively. It shows low correlation coefficient, that is, these multiple regression models can not represent the residual chlorine with the input parameters which varies independently with time changes related to weather condition. Artificial neural network models are applied with three different conditions. Input parameters are consisted of water quality data observed in water treatment process based on the structure of auto-regressive model type, considering a time lag. The artificial neural network models have better ability to predict residual chlorine at sediment basin than conventional linear and nonlinear multi-regression models. The determination coefficients of each model in verification process were shown as 0.742, 0.754, and 0.869, respectively. Consequently, comparing the results of each model, neural network can simulate the residual chlorine in sedimentation basin better than mathematical regression models in terms of prediction performance. This results are expected to contribute into automation control of water treatment processes.

• 한국수자원학회논문집
• /
• 제55권spc1호
• /
• pp.1283-1293
• /
• 2022

본 연구는 정수장의 수처리 공정에서 계측되고 있는 수량 및 수질데이터의 활용과 수처리 공정제어의 지능화를 위한 것으로 정수장에서 전염소 공정이 수반되는 처리공정에서 침전지 유출수 잔류염소농도 안정화를 위하여 이를 추정할 수 있는 모형을 구축하고자 하였다. 정수장 침전지 유출수의 잔류염소농도를 예측하기 위하여 중회귀모형과 인공지능 알고리즘 중 다층퍼셉트론 신경망, 랜덤포레스트 및 장단기기억(Long Short Term Memory; LSTM) 모형을 활용하였고 그 결과를 비교, 평가하였다. 모형의 입력변수로는 전염소 공정이 도입된 정수장에서의 잔류염소농도, 수온, 탁도, pH, 전기전도도, 유량, 알칼리도 등이 사용되었고 전염소에 따른 침전지의 안정적 운영을 위해 요구되는 침전지 잔류염소농도를 출력변수로 구성하였다. 적용 결과에서는 랜덤포레스트 모형이 가장 양호한 결과를 보여 주었으며 다음으로 LSTM, 다층퍼셈트론 신경망 순으로 나타났다. 수학적 모형인 중회귀모형은 적합도 측면에서 가장 낮은 결과를 보여 주었는데, 이는 수량과 수질데이터의 수치적인 규모나 차원의 차이뿐만 아니라 계절별 수질특성에 따라 염소소비 특성이 매우 다양하게 반응하기 때문으로 판단된다. 따라서 정수장 수처리 공정에서 인공지능 알고리즘의 적용을 위해서는 랜덤포레스트와 같이 의사결정 트리구조의 도입과 적용이 타당한 것으로 나타났다. 본 연구에서 분석된 결과를 근거로 전염소 공정이 도입된 정수장 수처리 공정에서 염소주입량을 실시간으로 예측 가능하게 함으로써 침전지 유출수에서 잔류염소농도를 일정하게 유지하는데 기여할 수 있을 것으로 기대된다.

• Preventive Nutrition and Food Science
• /
• 제21권2호
• /
• pp.147-154
• /
• 2016

In this study, the effects of a pre-filter system and electrolysis system on the safe and efficient reuse of brine in the cabbage salting process were investigated. First, sediment filter-electrolyzed brine (SF-EB) was selected as brine for reuse. Then, we evaluated the quality and microbiological properties of SF-EB and Chinese cabbage salted with SF-EB. The salinity (9.4%) and pH (4.63) of SF-EB were similar to those of control brine (CB). SF-EB turbidity was decreased (from 0.112 to 0.062) and SF-EB residual chlorine (15.86 ppm) was higher than CB residual chlorine (0.31 ppm), and bacteria were not detected. Salinity (2.0%), pH (6.21), residual chlorine (0.39 ppm), chromaticity, hardness, and chewiness of cabbage salted with SF-EB were similar to those of cabbage salted with CB. The total bacterial count in cabbage salted with CB was increased as the number of reuses increased (from 6.55 to 8.30 log CFU/g), whereas bacteria in cabbage salted with SF-EB was decreased (from 6.55 to 5.21 log CFU/g). These results show that SF-EB improved the reusability of brine by removing contaminated materials and by sterilization.

• 한국식품영양학회지
• /
• 제21권4호
• /
• pp.499-509
• /
• 2008

The purpose of this study was to investigate the changes in physicochemical and sensory properties of raw fruits during washing and chlorine treatments. Strawberry and banana were pre-prepared at different concentration of chlorinated water(0 ppm, 50 ppm and 100 ppm), immersion time(3 min and 5 min), and number of post-rinsing(1 time, 2 times and 3 times). The physicochemical properties such as pH, sugar contents, residual chlorine contents, color values and hardness of the fruits were analyzed, and the sensory quality were evaluated throughout the sterilization treatment process. After washing strawberry with 100 ppm chlorinated water and 3 times of post-rinsing, pH and residual chlorine contents were showed a little difference, while sugar contents, hardness, and color values(L, a and b) were reduced. In case of banana, pH, sugar contents and residual chlorine contents were not affected, and hardness and L color value were reduced. However, a and b color values of banana were gradually increased as the development of brown discoloration. Sensory properties of the samples were affected by the chlorine sterilization treatment. In overall acceptance, strawberry and banana treated with 100 ppm chlorinated water showed the lowest scores among treatments. Therefore it could be suggested that the application of 50 ppm chlorinated water for $3{\sim}5$ minutes with over 3 times of post-rinsing was the effective pre-preparation method without affecting the quality of the fruits.

• 해양환경안전학회지
• /
• 제2권1호
• /
• pp.89-95
• /
• 1996

This paper describes a fuzzy controlled pre-chlorination technique for purifying the pulluted raw water in water purification lants. For the purpose of obtaining the high quality water, the appropriate pre-chlorine dosage rate has to be continuously adjusted according to a change in quality of a intake raw water, weather, solar nergy mount, temperature and etc. Therefore, the method of expressing an expert's empirical knowledge cumulated from his past carrier by fuzzy reasoning and the fuzzy controller design technique is necessary.In this paper fuzzy membership functions and rules accordingto emprircal knowledge and experimental field data were obtained, And also fuzzy cintriller design using four feedforward components for the determination of pre-chlorine dosage rate and four feedback ones for the compensation of its dosage rate with residual chlorine and its change rate, was executed.

• 한국수자원학회논문집
• /
• 제57권3호
• /
• pp.151-164
• /
• 2024

상수도 공급을 위한 정수장에서 전염소 또는 중염소 공정이 도입된 수처리 공정의 염소농도 관리에 필요한 공정제어를 위하여 AI 기술을 활용한 수질예측 기법이 연구되고 있다. 본 연구에서는 정수장 수처리 공정에서 실시간으로 관측, 생산되고 있는 수량·수질자료를 이용하여 염소소독 공정제어 자동화를 목적으로 침전지 후단의 잔류염소 농도를 예측하기 위한 AI 기반 예측모형을 개발하였다. AI 기반 예측모형은 과거 수질 관측자료를 학습하여 이후 시점의 수질에 대한 예측이 가능한 기법으로, 복잡한 물리·화학·생물학적 수질모형과 달리 간단하고 효율적이다. 다중회귀 모형과 AI 기반 모형인 랜덤포레스트와 LSTM을 이용하여 정수장의 침전지 후단 잔류염소 농도를 예측하여 비교하였다. 최적의 잔류염소 농도 예측을 위한 AI 모형의 입출력 구조로는 침전지 전단의 잔류염소 농도, 침전지 탁도, pH, 수온, 전기전도도, 원수의 유입량, 알칼리도, NH₃ 등을 독립변수로, 예측하고자 하는 침전지 유출수의 잔류염소 농도를 종속변수로 선정하였다. 독립변수는 침전지 후단의 잔류염소에 영향이 있는 정수장에서 확보가 가능한 관측자료중에서 분석을 통해 선별하였으며, 분석 결과 연구대상 정수장인 정수장에서는 중회귀모형, 신경망모형, 모델트리 및 랜덤포레스트 모형을 비교한 결과 랜덤포레스트에 기반한 모형오차가 가장 낮게 도출되는 결과를 얻을 수 있었다. 본 연구에서 제시하는 침전지 후단의 적정 잔류염소 농도 예측값은 이전 처리단계에서 염소주입량의 실시간 제어가 가능토록 할 수 있어 수처리 효율 향상과 약품비 절감에 도움이 될 것으로 기대된다.

• 대한환경공학회지
• /
• 제22권3호
• /
• pp.505-510
• /
• 2000

본 연구는 부영양화시 다량 발생하고, 독소생성의 주원인 종으로 알려진 Microcystis aeruginosa의 정수처리 중 응집공정에서 전염소처리의 영향을 조사하였다. Microcystis aeruginosa를 실험실에서 배양하여, $10^5cell/mL$가 되도록 인공시료를 만들었다. 전염소처리의 염소주입량은 각각 0.2, 1.0, 10 mg-Cl/L으로 하였고, 반응시간은 1시간과 1분으로 하였다. 응집 후 모든 시료의 탁도는 응집제를 0.4 mg-Al/L 주입한 후 매우 낮게 나타났으므로 탁도 유발물질은 염소주입량에 의한 영향이 매우 낮은 것으로 나타났다. 염소량이 증가함에 따라 응집 후 잔류알루미늄은 감소하였고, $UV_{254}$는 증가하였다. 적당한 염소농도(1.0 mg-Cl/L)에서는 반응시간이 길어짐에 따라 $UV_{254}$가 증가하였다.

• 한국물환경학회지
• /
• 제38권6호
• /
• pp.267-274
• /
• 2022

This paper is a result of research conducted on the 800,000 m³/d capacity of A Water Treatment Plant (WTP) and 400,000 m³/d capacity of B WTP plant in operation in the Nakdong River region. We evaluated the effect of algae broom on the WTP operation based on the running data of both WTP and the data on the pre-oxidation process field test for algae control using sodium permanganate (SPM) at the B WTP. The study results showed that during the algal bloom period, the coagulant dose increased by 102% in A WTP and 58% in B WTP, respectively, and the chlorine dose also increased by 38% and 29%, respectively, which may affect Total trihalomethane (THM) production. Data such as algal populations and Chl-a, residual chlorine and THM, algal populations, and ozone dose appeared also highly correlated, confirming that algal broom affects WTP operations, including water quality and chemical dosage. As a result of the field test of B WTP, THMs appeared lower than that of the control, suggesting the possibility of the SPM pre-oxidation process as an alternative to algae-related water quality management. Furthermore, in terms of GHG emissions due to energy consumption, it was observed that the pre-oxidation process using SPM was approximately 10.8%, which is a very low ratio compared to the pre-ozonation process. Therefore, these results suggest that the SPM pre-oxidation process can be recommended as an alternative to low-carbon water purification technology.

• Environmental Engineering Research
• /
• 제24권3호
• /
• pp.501-512
• /
• 2019

The seasonal effects on the biostability of drinking water were investigated by comparing the seasonal variation of assimilable organic carbon (AOC) in full-scale water treatment process and adsorption of AOC by three filling materials in lab-scale column test. In full-scale, pre-chlorination and ozonation significantly increase $AOC_{P17\;(Pseudomonas\;fluorescens\;P17)}$ and $AOC_{NOX\;(Aquaspirillum\;sp.\;NOX)}$, respectively. AOC formation by oxidation could increase with temperature, but the increased AOC could affect the biostability of the following processes more significantly in winter than in warm seasons due to the low biodegradation in the pipes and the processes at low temperature. $AOC_{P17}$ was mainly removed by coagulation-sedimentation process, especially in cold season. Rapid filtration could effectively remove AOC only during warm seasons by primarily biodegradation, but biological activated carbon filtration could remove AOC in all seasons by biodegradation during warm season and by adsorption and bio-regeneration during cold season. The adsorption by granular activated carbon and anthracite showed inverse relationship with water temperature. The advanced treatment can contribute to enhance the biostability in the distribution system by reducing AOC formation potential and helping to maintain stable residual chlorine after post-chlorination.

• 한국환경보건학회지
• /
• 제46권6호
• /
• pp.710-718
• /
• 2020

Objectives: We analyzed water in waterscape facilities to investigate contamination levels of water-borne pathogens and four test items (pH, turbidity, residual chlorine, and Escherichia coli) at facilities including play fountains, splash parks, and artificial streams from June to October in Suwon City and in the whole of Gyeonggi-do. Methods: A total of 62 waterscape facility samples were collected from 36 sites and tested for pathogenic Escherichia coli and water-borne viruses that cause hand-foot-and-mouth disease, eye disease, and acute enteritis. Results: None of the water-borne pathogens were detected in waterscape facility samples collected from across Gyeonggi-do that were for pre-inspection for facility management. However, the results of samples from Suwon collected in hot weather and during the school vacation period showed five total inconsistencies in turbidity (four cases) and Escherichia coli (one case). Three out of the four inconsistent samples in turbidity were from the same facility which operated a sand filtration system due to its locational factors close to mountains. Conclusion: We suggest that the waterscape facilities in Gyeonggi-do are managed properly in the respect of microbial contamination and water quality.