• 한국기계가공학회지
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• 제13권4호
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• pp.56-68
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• 2014

This paper presents an experiment on the modeling, analysis, prediction and optimization of machining parameters used during the turning process of the low-carbon steel known as ST40. The parameters used to develop the model are the cutting speed, the feed rate, and the depth of the cut. The experiments were carried out under various conditions, with three level of parameters and two different treatments for each level (with and without a lubricant), to determine the effects of the parameters on the surface roughness and electric current consumption. These effects were investigated using response surface methodology (RSM). A second-order model is used to predict the values of the surface roughness and the electric current consumption from the results of experiments which collected preliminary data. The results of the experiment and the predictions of the surface roughness and electric current consumption under both treatments were found to be nearly identical. This result shows that the feed rate is the main factor that influences the surface roughness and electric current consumption.

• Journal of Biosystems Engineering
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• 제32권2호
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• pp.91-96
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• 2007

In this study, a prototype remote controlled weeder using solar module was developed and the evaluations of weeding, side walking and weeding performance were conducted to see if actual application was feasible in the paddy field. When traveling, the loss electric current was 8 to 15 A depending on operating and soil conditions. The average traveling speed was 0.25 m/s and the average slippage was 18%. When it side walked row by row, electric current consumption was 7 A on the average. When wheel rotors line went initially up and last down, electric current consumption was 12 to 15 A due to soil resistance. Electric current consumption when shifting wheel rotors line was less than 5 A due to no resistance. Field efficiency was 105 min/10a based on the test field. Operation was able to be done for 4.16 hours continually by 52 AH battery based on 300 W average maximum power consumption and 4.6 hours under sunny day considering solar module.

• 한국기계가공학회지
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• 제14권3호
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• pp.65-73
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• 2015

This paper presents a method of predicting the machining parameters on the turning process of low carbon steel using a neural network with back propagation (BP) and particle swarm optimization (PSO). Cutting speed, feed rate, and depth of cut are used as input variables, while surface roughness and electric current consumption are used as output variables. The data from experiments are used to train the neural network that uses BP and PSO to update the weights in the neural network. After training, the neural network model is run using test data, and the results using BP and PSO are compared with each other.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2011년도 춘계학술대회 논문집
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• pp.619-626
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• 2011

In this paper, while electric multiple unit is moving on the rail, the content of measuring and analysing electric power consumption is mentioned. In order to measure the electric power consumption, we developed the power record analysis equipment and installed it the inside of the converter and inverter system to record the electric power consumption measured by voltage sensor and current sensor. Moving on the rail, we analysed traction power used up and regenerative power by using the measuring instrument. We expect that the measured and analysed data will offer basic research material to devise a energy reduction plan and introduce a new EMU system with high efficiency.

• Membrane and Water Treatment
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• 제1권1호
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• pp.13-37
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• 2010

The performance of an electrodialyzer for concentrating seawater is predicted by means of a computer simulation, which includes the following five steps; Step 1 mass transport; Step 2 current density distribution; Step 3 cell voltage; Step 4 NaCl concentration in a concentrated solution and energy consumption; Step 5 limiting current density. The program is developed on the basis of the following assumption; (1) Solution leakage and electric current leakage in an electrodialyzer are negligible. (2) Direct current electric resistance of a membrane includes the electric resistance of a boundary layer formed on the desalting surface of the membrane due to concentration polarization. (3) Frequency distribution of solution velocity ratio in desalting cells is equated by the normal distribution. (4) Current density i at x distant from the inlets of desalting cells is approximated by the quadratic equation. (5) Voltage difference between the electrodes at the entrance of desalting cells is equal to the value at the exits. (6) Limiting current density of an electrodialyzer is defined as average current density applied to an electrodialyzer when current density reaches the limit of an ion exchange membrane at the outlet of a desalting cell in which linear velocity and electrolyte concentration are the least. (7) Concentrated solutions are extracted from concentrating cells to the outside of the process. The validity of the computer simulation model is demonstrated by comparing the computed results with the performance of electrodialyzers operating in salt-manufacturing plants. The model makes it possible to discuss optimum specifications and operating conditions of a practical-scale electrodialyzer.

• 한국의류산업학회지
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• 제4권6호
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• pp.550-556
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• 2002

The changes of the main body temperature of a I tube 2 chamber bent silkworm type dyeing machine and the reduction of energy consumption of the dyeing machine by the energy saving design are reported. This dyeing machine was developed for the purpose of the energy saving and high efficiency. In this study, the changes of the main body temperature of the 1 tube 2 chamber bent silkworm type dyeing machine were studied experimentally. Especially the effect of the blower motor electric current and the main body pressure at various blower frequencies were studied experimentally. In the experimental data for the changes of main body temperature, it was shown that the main body temperature increased as the blower motor electric current and the main body pressure increased.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제5권7호
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• pp.1274-1292
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• 2011

Due to the variety of household electric devices and different power consumption habits of consumers at present, general home energy management (HEM) systems suffer from the lack of dynamic identification of various household appliances and a unidirectional information display. This study presented a set of intelligent interconnection network systems for electric appliances, which can measure the power consumption of household appliances through a current sensing device based on OSGi platform. The system establishes the characteristics and categories of related electric appliances, and searches the corresponding cluster data and eliminates noise for recognition functionality and error detection mechanism of electric appliances by applying the clustering algorithm. The system also integrates household appliance control network services so as to control them according to users' power consumption plans or through mobile devices, thus realizing a bidirectional monitoring service. When the system detects an abnormal operating state, it can automatically shut off electric appliances to avoid accidents. In practical tests, the system reached a recognition rate of 95%, and could successfully control general household appliances through the ZigBee network.

• 한국신재생에너지학회:학술대회논문집
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• 한국신재생에너지학회 2007년도 추계학술대회 논문집
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• pp.152-155
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• 2007

Fuel cell electric vehicles (FCEVs) using hydrogen gas are zero emission vehicles, thus emission measurement for combustion vehicles is not applicable. The hydrogen gas consumption for fuel economy will be measured by the stabilized pressure/temperature method, mass flow method and electrical current method, etc. In this research, weight method with a newly manufactured test equipment is applied to measure the hydrogen consumption because above 3-methods have a deviation. The hydrogen consumption is directly calculated by the weight differences of the external hydrogen tank before and after the chassis dynamometer test. Ultimately the fuel economy for FCEVs is obtained with a deviation less than 1% in all chassis dynamometer tests.

• 전기전자학회논문지
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• 제22권3호
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• pp.878-881
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• 2018

In this paper, experiments through performance evaluation under real operation environment were conducted. Transceiver and microcontroller shows the characteristics for the amount of current consumption and software protocol was optimized by controlling the time of Report Attribute and electric current level. To reduce current consumption when using battery, with designing transmission of the same amount of data as soon as possible, power consumption efficiency was enhanced.

• 한국분무공학회지
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• 제29권1호
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• pp.1-6
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• 2024

This paper is a numerical analysis study for evaluating the energy efficiency of electric vehicles. Currently, the methods for testing and evaluating the energy consumption efficiency of electric vehicles have limitations such as resources and time. Therefore, there is a need for research on developing models to predict the energy consumption efficiency of electric vehicles. In this study, a numerical analysis research is conducted to predict the energy efficiency of electric vehicles using a vehicle dynamics numerical analysis model. To validate the accuracy of the simulation model, it is compared the results of dynamometer tests with the simulation results and used the Unified Diagnostic Services (UDS) protocol to acquire internal data from the electric vehicle. It is ensured the reliability of the simulation model by comparing data such as motor speed, battery voltage, current, state of charge (SOC), regenerative braking power generation, and total driving distance of the test vehicle with dynamometer test data and simulation model results.