• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.170.4-170
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• 2001

Safety and confidence of the communications network is the main purpose for the unmanned control systems, in terms of appling a satellite communications network to the water treatment and supply plant communication system. Since the unmanned control systems were applied in the industrial site, the lack of confidence on the communications network has been presented continuously as a main problem for the unmanned and automation systems. Therefore, satellite communications network was presented as one of the methods to solve this problem, supporting the wire used telecommunication. In addition to the safety of a communications network, there is the retrenchment of expenditure. This dual communications network has ...

• 한국수자원학회논문집
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• 제48권10호
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• pp.845-855
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• 2015

대규모 상수관망 시스템의 운영비용 절감을 위한 펌프장 운영 최적화 연구가 최근 활발히 진행되고 있다. 이러한 상수관망 시스템 운영 최적화에 대한 연구를 수행하기 위해서는 짧게는 24시간, 길게는 1주일 이상의 시간모의가 필수적이며, 최적화 알고리즘과의 연계를 통한 시뮬레이션이 요구된다. 대규모 상수관망의 경우 관로 및 절점의 수가 수 천 혹은 수 만개에 달해 수리해석 및 최적화에 많은 시간이 소요되며 실시간 운영을 목적으로 하는 경우 모형의 적용에 한계가 발생한다. 이처럼 모의시간에 대한 문제를 해결하기 위해서는 해당 상수관망 시스템의 수리 거동, 수질 해석 결과를 변화시키지 않는 범위에서 관망을 간소화 할 필요가 있다. 본 연구에서는 국내에서 실제로 운영되고 있는 송, 배수 시스템의 일부를 대상으로 시스템 간소화, 즉 골격화(Skeletonization) 연구를 진행하였으며, 모두 네 가지의 골격화 기법을 비교, 평가하였다. 본 연구에서 제안된 골격화 기법을 통해 대규모 상수관망의 해석에 소요되는 시간을 단축함으로써, 실제 상수관망의 실시간 운영 모듈 개발에 도움이 될 것으로 기대한다.

• 제어로봇시스템학회논문지
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• 제10권6호
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• pp.551-556
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• 2004

Coagulation process is one of the most important processes in water treatment procedures for stable and economical operation, and coagulant dosing of this process for most plants is generally determined by the jar test. However, this method does not only take a long time to analyze and get the result but also has difficulties in applying to automatic control. This paper shows the feasibility of applying neural network to control the coagulant dosing automatically in water treatment plant. To be specific, the predicted results of the neural network model is shown to be similar to that of jar test. The input variables for learning the neural network are turbidity, water temperature, pH, and alkalinity. Combining the neural network and SCD(Streaming Current Detector) for feedforward and feedback control of injecting coagulant, a rapid change of the raw water quality can be accommodated.

• 한국물환경학회지
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• 제29권1호
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• pp.55-65
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• 2013

It is very difficult to apply stream flow data directly to the management of Total Maximum Daily Loads because there are some differences between the unit watershed and the stream flow monitoring network in their characteristics such as monitoring locations and its intervals. Flow duration curve can be developed by linking the daily flow data of stream monitoring network to 8 day interval flow data of the unit watershed. This study investigated the current operating conditions of the stream flow monitoring network and the flow relationships between the unit watershed and the stream flow monitoring network. Criteria such as missing and zero value data, and correlation coefficients were applied to select the stream flow reference sites. The reference sites were selected in 112 areas out of 142 unit watersheds in 4 river basins, where the stream flow observations were carried out in relatively normal operating conditions. These reference sites could be utilized in various ways such as flow variation analysis, flow duration curve development and so on for the management of Total Maximum Daily Loads.

• 한국수자원학회논문집
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• 제32권2호
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• pp.143-152
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• 1999

우리나라 경북 동·남부지역은 지형조건과 원래 부족한 수자원으로 용수개발에 어려움을 겪는 지역이다. 이와 같은 물 문제를 완화시키기 위해 새로운 댐의 개발과 광역용수공급, 기존 용수공급 시스템의 조정, 오래된 댐의 개·증축 그리고 저류용댐의 건설 방안이 검토되었다. 새롭게 제시된 수자원 개발 대안의 평가는 수자원 시스템의 의사결정 도구로 많이 이용되고 있는 수학적 모형의 하나인 네트워크 최적화 모형을 이용하였다. 연구결과 용수공급 시스템이 2011년까지 건설된다면 포항 및 경주권의 용수공급 신뢰도는 95% 이상을 확보할 수 있을 것으로 분석되었으며 네트워크 최적화 모형이 수리권 혹은 용수공급 우선 순위를 고려한 수자원 시설물의 운영을 분석하는데 사용 될 수 있을 것으로 판단된다.

• Journal of Electrical Engineering and Technology
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• 제9권3호
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• pp.893-898
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• 2014

Recently, the interior permanent synchronous motor (IPMSM) has been applied to an integrated starter and generator (ISG) for hybrid electric vehicles. In the design of such a motor, thermal analysis is necessary to maximize the power density because the loss is proportional to the power of a motor. Therefore, a cooling device as a heat sink is required internally. Generally, a cooling system designed with a water jacket structure is widely used for electric motors because it has advantages of simple structure and cooling effectiveness. An effective approach to analyze an electric machine with a water jacket is a thermal equivalent network. This network is composed of thermal resistance, a heat source, and thermal capacitance that consider the conduction, convection, and radiation. In particular, modeling of the cooling channel in a network is challenging owing to the flow of the coolant. In this paper, temperature prediction using a thermal equivalent network is performed in an ISG that has a water cooled system. Then, an experiment is conducted to verify the thermal equivalent network.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권6호
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• pp.2925-2948
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• 2019

In order to improve the utilization of irrigation water resources of greenhouse tomatoes, a water-saving irrigation decision-making model based on genetic optimization T-S fuzzy neural network is proposed in this paper. The main work are as follows: Firstly, the traditional genetic algorithm is optimized by introducing the constraint operator and update operator of the Krill herd (KH) algorithm. Secondly, the weights and thresholds of T-S fuzzy neural network are optimized by using the improved genetic algorithm. Finally, on the basis of the real data set, the genetic optimization T-S fuzzy neural network is used to simulate and predict the irrigation volume for greenhouse tomatoes. The performance of the genetic algorithm improved T-S fuzzy neural network (GA-TSFNN), the traditional T-S fuzzy neural network algorithm (TSFNN), BP neural network algorithm(BPNN) and the genetic algorithm improved BP neural network algorithm (GA-BPNN) is compared by simulation. The simulation experiment results show that compared with the TSFNN, BPNN and the GA-BPNN, the error of the GA-TSFNN between the predicted value and the actual value of the irrigation volume is smaller, and the proposed method has a better prediction effect. This paper provides new ideas for the water-saving irrigation decision in greenhouse tomatoes.

• 한국물환경학회지
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• 제27권3호
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• pp.334-341
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• 2011

The free residual chlorine of tap water samples, collected from 266 faucets on the water pipe network in Daegu City, was between 0.1 and 0.79 mg/L. On microorganic tests, general bacteria and the coliform goup were not detected and thus the tap water was turned out to be fit to drink. In particular, samples of which free residual chlorine was 0.1 mg/L and over were cultured in R2A agar media at $25^{\circ}C$ for 7 days, and as a result heterotrophic bacteria were detected in 65.9% of samples; (1). The closer tap water got to the faucet from the stilling basin, the lower residual chlorine concentration became but the more the bacterial count became. And, more bacteria were detected in the R2A agar medium than in the PCA medium. (2). In the case of separated strains, most colonies were reddish or yellowish. 16S rRNA sequence was identified as Methylobacterium sp. and Williamsia sp., and yellow strain was identified as Sphingomonas sp., Sphingobium sp., Novosphingobium sp., Blastomonas sp., Rhodococcus sp. and Microbacterium sp. White strain was identified as Staphylococcus sp. (3). Sterilized tap water in polyethylene bottles was inoculated with separated strain and was left as it was for 2 months. As a result, bio-film was observed in tap water inoculated with Methylobacterium sp. and Sphingomonas sp. It was found that heterotrophic bacteria increased when free residual chlorine was removed from tap water in the water pipe network. Thus, there is a need to determine a base value for heterotrophic bacteria in order to check the cleanliness of tap water in the water pipe network.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1995년도 Proceedings of the Korea Automation Control Conference, 10th (KACC); Seoul, Korea; 23-25 Oct. 1995
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• pp.75-78
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• 1995

In this paper it is concerned to develop control method using jar-test results in order to predict the optimum dosage of coaglant, PAC(PoliAluminum Chloride). Considering the relations with the reactions with the reaction of coagulation and flocculation, the five independent variables ( e, g, turbidity of raw water, water turbidity in flocculators, temperature, pH, and alkalynity) are selected out of parameters and they are put into calculation to develop a neural network model for PAC dosing process in water purification system. This model is utilized to predict optimum dosage of PAC. That is, the optimum dosage of PAC is searched in neural network model for PAC dosing process to minimize the water turbidity in flocculators. This searching is implemented by means of expert heuristics. The efficacy of the proposed contorl schemem and feasibility of acquired neural network model for PAC dosing contorl in water purification system is evaluated by means of computer simulation.

• 한국농공학회논문집
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• 제63권4호
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• pp.23-32
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• 2021

For agricultural water management, it is essential to establish the digital infrastructure data such as agricultural watershed, irrigated area and canal network in rural areas. Approximately 70,000 irrigation facilities in agricultural watershed, including reservoirs, pumping and draining stations, weirs, and tube wells have been installed in South Korea to enable the efficient management of agricultural water. The total length of irrigation and drainage canal network, important components of agricultural water supply, is 184,000 km. Major problem faced by irrigation facilities management is that these facilities are spread over an irrigated area at a low density and are difficult to access. In addition, the management of irrigation facilities suffers from missing or errors of spatial information and acquisition of limited range of data through direct survey. Therefore, it is necessary to establish and redefine accurate identification of irrigated areas and canal network using up-to-date high resolution images. In this study, previous existing data such as RIMS (Rural Infrastructure Management System), smart farm map, and land cover map were used to redefine irrigated area and canal network based on appropriate image data using satellite imagery, aerial imagery, and drone imagery. The results of the building the digital infrastructure in rural areas are expected to be utilized for efficient water allocation and planning, such as identifying areas of water shortage and monitoring spatiotemporal distribution of water supply by irrigated areas and irrigation canal network.