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토석류 모니터링 계측자료 신뢰도 향상을 위한 중앙값필터와 칼만필터 적용
김종락(Kim, Jongrack),유광태(You, Kwangtae),장수현(Jang, Suhyun),박기정(Pak, Gijung),이득수(Pak, Gijung) 한국방재학회 2017 한국방재학회논문집 Vol.17 No.1
원격 모니터링 시스템에서 계측되는 자료는 다양한 요인에 의해 이상값 및 잡음을 포함하게 된다. 정확한 분석을 위해서는 계측자료의 신뢰도가 매우 중요하다. 본 연구에서는 계측자료의 신뢰도 확보를 위해 이상값 제거에 개선된 중앙값 필터 알고리즘, 잡음 제거에 칼만필터 알고리즘을 함께 사용할 것을 제안하였다. 제안한 알고리즘을 현장 계측 자료에 적용한 결과, 잡음과 이상값을 모두 제거하였으며, 채널당 연산 시간이 1밀리초 이하로 매우 빨라 저사양 계측모듈에 쉽게 적용 가능함을 확인하였다. The data measured in the remote monitoring system will contain outlier values and noise due to various factors. Reliability of measured data is important for accurate analysis. In this study, we propose the use of an improved median filtering algorithm to remove outlier data, and Kalman filter algorithm to remove noise. After applying to the field measurement data, the proposed algorithm removed both outlier values and noise, and it was confirmed that the calculation time per channel was significantly low, at less than 1 millisecond, thus it can be easily applied to the low measurement module.
하수처리공정 모의시간 단축을 위한 개선된 뉴턴-랩슨 방법 개발 및 평가
김종락(Kim, Jongrack),유광태(You, Kwangtae),표우원화(Piao, Wenhua),김예진(Kim, Yejin) 한국방재학회 2018 한국방재학회논문집 Vol.18 No.5
유입수질 변동은 하수처리공정의 성능을 좌우하는 대표적 외란으로, 유입수질 변동에 따른 공정의 최적운전을 위해서는 공정 제어의 적용이나 최적운전방안 도출을 위한 공정 모의가 필수적이다. 공정 모의를 위해 현재 전 세계적으로 널리 사용되는 질소·인 제거공정 모델에는 IWA의 ASM2d 모델이 있고, 바이오가스 생산공정의 모의를 위해서는 ADM1 모델이 사용되며, 이들 모델은 상미분방정식으로 이루어져 있다. 하나의 하수처리장을 모의하는 데 있어 주어진 일련의 외란 조건과 운전 조건 하에서 공정의 정상상태를 모사하는 단계는 필수적인데, 이 때 상미분방정식를 해석하는 단계에서 연산시간이 오래 걸리는 단점이 존재한다. 연산시간을 단축하기 위해 본 연구에서는 상미분방정식 해석과 뉴턴-랩슨 알고리즘을 결합한 개선된 뉴턴-랩슨 방법을 제안하였다. 제안된 방법으로 공정을 모의한 결과, 상미분방정식 해석만을 적용하는 것과 비교할 때 ASM2d는 32.3배, ADM1은 8배 빠른 속도로 연산을 수행할 수 있었다. In order to optimize the process operation against fluctuating influent water quality, it is essential to apply process control and simulate the process for deriving the optimal operation method. To simulate the process, the ASM2d model and ADM model of the IWA have been widely used for the simulation of the nitrogen and phosphorus removal process and biogas production process, which consist of ordinary differential equations. In order to simulate a sewage treatment plant, it is essential to simulate the steady state of a process under a given set of disturbances and operating conditions. However, the disadvantage is that the calculation time is long when analyzing the ordinary differential equations. In order to shorten the computation time, we propose an improved Newton-Raphson method. As a result, the ASM2d and the ADM1 were able to simulate the processes 32.3 times and 8 times faster than ordinary differential equation analysis, respectively.
김종락 ( Jongrack Kim ),이가희 ( Gahee Rhee ),유광태 ( Kwangtae You ),김동윤 ( Dongyoun Kim ),이호식 ( Hosik Lee ) 한국물환경학회 2020 한국물환경학회지 Vol.36 No.6
This study aims to conserve and monitor energy use in public sewage treatment plants by utilizing data from the SCADA system and by controlling the aeration rate required for maintaining effluent water quality. Power consumption in the sewage treatment process was predicted using the equipment’s uptime, efficiency, and inherent power consumption. The predicted energy consumption was calibrated by measured data. Additionally, energy efficiency indicators were proposed based on statistical data for energy use, capacity, and effluent quality. In one case study, a sewage treatment plant operated via the SBR process used∼30% of energy consumed in maintaining the bioreactors and treated water tanks (included decanting pump and cleaning systems). Energy consumption analysis with the K-ECO Tool-kit was conducted for unit processing. The results showed that about 58.7% of total energy consumed was used in the preliminary and biological treatment rotating equipment such as the blower and pump. In addition, the energy consumption rate was higher to the order of 19.2% in the phosphorus removal process, 16.0% during sludge treatment, and 6.1% during disinfection and discharge. In terms of equipment energy usage, feeding and decanting pumps accounted for 40% of total energy consumed following 27% for blowers. By controlling the aeration rate based on the proposed feedback control system, the DO concentration was reduced by 56% compared pre-controls and the aeration amount decreased by 28%. The overall power consumption of the plant was reduced by 6% via aeration control.
확률밀도함수 기반 유입하수 재현 및 활성슬러지공정 설계기법 개발
유광태 ( Kwangtae You ),김종락 ( Jongrack Kim ),윤주환 ( Zuhwan Yun ),박기정 ( Gijung Pakt ) 한국물환경학회 2017 한국물환경학회지 Vol.33 No.2
An important factor in determining the design and, therefore, the efficiency of wastewater treatment plants (WWTPs) is the influents` quantity and quality. Detailed and accurate information is essential for process control, diagnosis, and operation. In designing a plant, the optimal capacity of each bioreactor must be determined. Probabilistic models are used to predict the wastewater quantity and quality of WWTPs, which are widely used to improve plant designs and operations. In this study, the optimal probability distribution of time series data was derived to predict the influent`s water quantity and quality. Wastewater data were generated using a Monte Carlo simulation. In addition, we estimated various alternatives for the improvement of bioreactor operations based on present operation conditions, using the generated influent data and the activated sludge model, and suggested an alternative for an optimally effective plant operation. Since the influent quantity and quality were highly correlated with the actual operation data, the WWTPs` real influent characteristics were well reproduced. Adopting this suggested alternative will improve the operating conditions of WWTPs and an improvement plan for the current tele monitoring system`s effluent quality standards can be proposed.