• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.4
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• pp.493-499
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• 2022

The standards pertaining to the quality of discharged water in sewage treatment plants are strengthening, and accordingly, facilities in sewage treatment plants are being upgraded. In addition, the discharge water quality of sewage treatment plants must be maintained at a high level, and efficient sewage treatment plant operations have thus emerged as a very important issue. For the efficient operation of sewage treatment plants, this study applied a basic blowing amount calculation method based on sewage facilities to evaluate the required oxygen amount and blowing amount according to inflow water quality by logicizing various influencing factors. As a result of calculating the amount of air blown by applying actual April water quality data from sewage treatment plant A to the blower demand calculation developed through this study, it was found that the average amount of air blown was reduced by about 12%. When the blower demand calculation developed here is applied to an actual sewage treatment plant, the amount of air blown can be controlled based on the inflow water quality. This can facilitate the realization of an autonomous control of sewage treatment plants, in contrast to the existing sewage treatment operation method that relies on operational experience of operator. In addition, it is expected that efficient sewage treatment plants can be operated by reducing blowing amounts and power costs, which will contribute to both energy and carbon savings.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2000.11b
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• pp.354-362
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• 2000

In Korea, researches on year-round leaf vegetables production system are in progress, most of them focused on environmental control. Therefore, automation technologies for harvesting, transporting, and grading are in great demand. A robot system for harvesting lettuces, composed of a 3-DOF (degree of freedom) manipulator, an end-effector, a lettuce feeding conveyor, an air blower, a machine vision system, six photoelectric sensors, and a fuzzy logic controller, was developed. A fuzzy logic control was applied to determine appropriate grip force on lettuce. Leaf area index and height were used as input variables and voltage as an output variable for the fuzzy logic controller. Success rate of the lettuce harvesting was 94.12%, and average harvesting time was approximately 5 seconds per lettuce.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.23 no.6
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• pp.441-448
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• 2011

The energy consumption of a condensing gas boiler may be greatly reduced by the effective operation of the unit. In this study, the supply water algorithm for a condensing gas boiler control was developed by using the fuzzy logic. This includes the supply water set temperature algorithm, and the control algorithms of a gas valve, a blower and a pump. For the set temperature algorithm, the outside air temperature and the return water temperature were used as input variables. The supply water temperature difference and its slope were used as input variables of the gas valve and blower control algorithm. And the supply water temperature and the return water temperature were used as input variables of the pump control algorithm. In order to analyse performances of these algorithms, the dynamic model of a condensing gas boiler was used. The initial start-up test, the supply water set temperature change test, the outside air temperature change test, and the return water temperature change test were performed. Simulation results showed that algorithms developed in this study may be practically applied for the effective control of a condensing gas boiler.

• Journal of Biosystems Engineering
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• v.25 no.1
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• pp.63-70
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• 2000

In Korea, researches for year-round leaf vegetables production system are in progress and the most of them are focused on environment control. Automation technologies for harvesting , transporting and grading need to be developed. This study was conducted to develop harvesting process automation system profitable to a competitive price. 1. Manipulator and end-effector are to be designed and fabricated , and fuzzy logic controller for controlling these are to be composed. 2. The entire system constructed is to be evaluated through a performance test. A robot system for harvesting a lettuce was developed. It was composed of a manipulator with 20DOF (degrees of freedom) an end-effector, a lettuce feeding conveyor , an air blower , a machine vision device, 6 photoelectric sensors and a fuzzy logic controller. A fuzzy logic control was applied to determined appropriate grip force on lettuce. Leaf area index and height index were used as input parameters, and voltage was used as output parameter for the fuzzy logic controller . Success rate of the lettuce harvesting system was 93.06% , and average harvesting time was about 5 seconds per lettuce.

• International Journal of Advanced Culture Technology
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• v.4 no.2
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• pp.47-56
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• 2016

In transformer cooling systems, oil temperature is controlled through the use of a blower and oil pump. For this paper, set-point algorithms, a reset algorithm and control algorithms of the cooling system were developed by neural networks and fuzzy logics. The oil inlet temperature was set by a $2{\times}2{\times}1$ neural network, and the oil temperature difference was set by a $2{\times}3{\times}1$ neural network. Inputs used for these neural networks were the transformer operating ratio and the air inlet temperature. The inlet set temperature was reset by a fuzzy logic based on the transformer operating ratio and the oil outlet temperature. A blower was used to control the inlet oil temperature while the oil pump was used to control the oil temperature difference by fuzzy logics. In order to analysis the performance of these algorithms, the initial start-up test and the step change test were performed by using the dynamic model of a transformer cooling system. Test results showed that algorithms developed for this study were effective in controlling the oil temperature of a transformer cooling system.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.22 no.8
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• pp.515-522
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• 2010

In order to improve the efficiency of a transformer cooling system, the intelligent algorithm was developed. The intelligent algorithm is composed of a setpoint algorithm and a control algorithm. The setpoint algorithm was developed by the neural network, and the control algorithm was developed by the fuzzy logic. These algorithms were used for the control of a blower and an oil pump of the transformer cooling system. In order to analyse performances of these algorithms, the dynamic model of a transformer cooling system was used. Based on various performance tests, energy savings and stable controls of a transformer cooling system were observed. Therefore, control algorithms developed for this study may be effectively used for the control of a transformer cooling system.

• Proceedings of the SAREK Conference
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• 2008.11a
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• pp.399-404
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• 2008

Condensing gas boiler units may make a big role for the reduction of energy consumption in heating industries. In order to decrease the energy consumption of a condensing gas boiler unit, the effective control of the system is necessary. In this study, control algorithms of a condensing gas boiler were developed. Control algorithms are composed of the setpoint algorithm and the control algorithm. The setpoint algorithm consists of the supply water temperature setpoint algorithm and the pump setpoint algorithm. The control algorithm consists of the gas valve control algorithm and the blower control algorithm. In order to analyse the performance of control algorithms, dynamic models of a condensing gas boiler system were used. Simulation results showed that control algorithms developed for this study may be practically applied to the condensing gas boiler.

• Applied Chemistry for Engineering
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• v.16 no.2
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• pp.217-225
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• 2005

Because of the limitation of controllable operation variables for the wastewater treatment process with variable hydrodynamic flow patterns, it may preclude the use of this type of nutrient removal activated sludge process. As the operation variables, only temperature and dissolved oxygen (DO) have been used to operate the process. This study made an effort to improve treatment efficiency and operability of the process by the following methodologies: 1) process and operation data analysis using process simulation, 2) determination of optimal control logic or algorithm using a pilot-scaled experimental apparatus and its operations, and 3) application of experimental and simulation results to find the optimal process operation modes. In this study, it was found that the optimal operation mode named 'save mode' in the basis of process variables, such as the ammonia-nitrogen concentration of inlet flow, temperature and flow rate, can reduce the operation cost comparing with the present normal operation mode. And the stable conditions in nitrification were also shown by the proportional control of DO with the inlet air flow rate of blower and the mixing rate of mechanical aeration.