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RISS 인기검색어
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- 저자 : 나상건(Sang-Gun Na) (검색결과 4 건)
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보일러 연소 모델의 자동 갱신 기능을 가지는 화력발전소 보일러 연소 최적화 기법 적용 결과
나상건(Sang-Gun Na),이정식(Jung-Sik Lee),맹좌영(Jwa-young Maeng) 대한기계학회 2022 대한기계학회 춘추학술대회 Vol.2022 No.11
In this study, a combustion optimization technique with a function of automatically updating the boiler combustion model is introduced. Combustion optimization technique controls the combustion of a boiler in a thermal power plant to reduce pollutants and increase combustion efficiency, ultimately reducing fuel consumption, increasing boiler efficiency, and reducing the cost of treating pollutants. Multi-Layer Perceptron (MLP), an artificial neural network model, was used for the boiler combustion model, and Particle Swarm Optimization (PSO) was used for the optimization algorithm. Boiler combustion model is managed by model management module that automatically creates/selects/updates/deletes. This model management module was able to continuously update the model by using the operation data generated in real time. In addition, an output controller that converts the optimum combustion control value derived by this technique into a stable control signal value of the power plant controller was added to enable safe connection with the power plant controller. This technique confirmed the performance by linking with actual control in the form of S/W solution of edge computing server for thermal power plants in India. The plant has a capacity of 660 MW and the boiler is tangential firing type. In addition, the performance of this technique was verified by linking the control to the opposite firing boiler of the domestic USC 1000 MW thermal power plant.
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보일러 연소 모델의 자동 갱신 기능을 가지는 화력발전소 보일러 연소 최적화 기법 적용 결과
나상건(Sang-Gun Na),이정식(Jung-Sik Lee),맹좌영(Jwa-young Maeng) 대한기계학회 2022 대한기계학회 춘추학술대회 Vol.2022 No.11
In this study, a combustion optimization technique with a function of automatically updating the boiler combustion model is introduced. Combustion optimization technique controls the combustion of a boiler in a thermal power plant to reduce pollutants and increase combustion efficiency, ultimately reducing fuel consumption, increasing boiler efficiency, and reducing the cost of treating pollutants. Multi-Layer Perceptron (MLP), an artificial neural network model, was used for the boiler combustion model, and Particle Swarm Optimization (PSO) was used for the optimization algorithm. Boiler combustion model is managed by model management module that automatically creates/selects/updates/deletes. This model management module was able to continuously update the model by using the operation data generated in real time. In addition, an output controller that converts the optimum combustion control value derived by this technique into a stable control signal value of the power plant controller was added to enable safe connection with the power plant controller. This technique confirmed the performance by linking with actual control in the form of S/W solution of edge computing server for thermal power plants in India. The plant has a capacity of 660 MW and the boiler is tangential firing type. In addition, the performance of this technique was verified by linking the control to the opposite firing boiler of the domestic USC 1000 MW thermal power plant.
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SVDD기법을 이용한 하이브리드 전기자동차 충-방전시스템의 고장검출 알고리듬
나상건(Na, Sang-Gun),양인범(Yang, In-Beom),허훈(Heo, Hoon) 한국소음진동공학회 2011 한국소음진동공학회 논문집 Vol.21 No.11
A fault detection algorithm of a charge and discharge system to ensure the safe use of hybrid electric vehicle is proposed in this paper. This algorithm can be used as a complementary way to existing fault detection technique for a charge and discharge system. The proposed algorithm uses a SVDD technique, which additionally utilizes two methods for learning a large amount of data; one is to incrementally learn a large amount of data, the other one is to remove the data that does not affect the next learning using a new data reduction technique. Removal of data is selected by using lines connecting support vectors. In the proposed method, the data processing speed is drastically improved and the storage space used is remarkably reduced than the conventional methods using the SVDD technique only. A battery data and speed data of a commercial hybrid electrical vehicle are utilized in this study. A fault boundary is produced via SVDD techniques using the input and output in normal operation of the system without using mathematical modeling. A fault detection simulation is performed using both an artificial fault data and the obtained fault boundary via SVDD techniques. In the fault detection simulation, fault detection time via proposed algorithm is compared with that of the peak-peak method. Also the proposed algorithm is revealed to detect fault in the region where conventional peak-peak method is never able to do.
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듀얼 서보모터 구동형 프레스 시스템의 동기화 제어기법 연구
나상건(Sang-Gun Na),권오신(O-Shin Kwon),강재훈(Jae-Hoon Kang),허훈(Hoon Heo) 한국생산제조학회 2013 한국생산제조학회지 Vol.22 No.2
In this paper, a synchronization control technique of dual-servo motor driven press system is proposed. An independent cascade PID control technique has been applied to the conventional press system for advancement of control stability. However, it is not easy to reduce synchronous error using the independent cascade PID control technique when some different load disturbances are involved in each motor. The eccentric error of the slide caused by the problem degrade the control performance of the BDC(Bottom Dead Center). In order to achieve reduction of the synchronous error between two servo motors and accurate position control simultaneously, a new control scheme comprised with cascade PID control loop and cross-coupling loop is proposed. In simulation using Matlab SIMULINK, the AC servo system is designed. The control performance of proposed technique is compared with conventional control technique to the model of AC servo system. Also, the sub-scale model of dual-servo motor driven press system which can replicate the slide motion is constructed for experimental verification for the performance of the proposed control technique. The cross-coupling control technique reveals more precise and stable performances in the position and synchronization controls.
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