• Transactions of the Korean Society of Mechanical Engineers B
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• v.40 no.5
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• pp.297-304
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• 2016

When a control algorithm is developed to protect automotive compressor surges, the simulation model typically selects an empirically determined look-up table. However, it is difficult for a control oriented empirical model to show surge characteristics of the super charger. In this study, a dynamic supercharger model is developed to predict the performance of a centrifugal compressor under dynamic load follow-up. The model is developed using Simulink$^{(R)}$ environment, and is composed of a compressor, throttle body, valves, and chamber. Greitzer's compressor model is used, and the geometric parameters are achieved by the actual supercharger. The simulation model is validated with experimental data. It is shown that compressor surge is effectively predicted by this dynamic compressor model under various operating conditions.

• Proceedings of the SAREK Conference
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• 2009.06a
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• pp.539-543
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• 2009

When the suction pressure of compressor decreases under its limit, the compression ratio is increased causing the malfunctions of compressor. As the method to decrease the compression ratio, hot gas bypass system is usually adopted in heat pump system. In the hot gas bypass system, the discharged gas from the compressor is bypassed into the compressor suction, which causes the increase of suction pressure and the decrease of compression ratio. In this study, the characteristics and performances of the hot gas bypass system in heat pump was investigated experimentally with a variation of the bypass flow rate ratio. With the increase of the bypass rate ratio, the compressor suction pressure was increased, even though the total capacity and COP was decreased. From the analysis of the experimental results, the optimum pressure control algorithm was suggested in this study.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.17 no.8
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• pp.780-788
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• 2005

Two different types of algorithms were developed and applied to detect the partial faults of a multi-type air conditioning system. Partial faults include the compressor valve leakage, the refrigerant pipe partial blockage, the condenser fouling, and the evaporator fouling. The first algorithm was developed by using mathematical models and parity relations, and the second algorithm was developed by using mathematical models and a RBF neural network. Test results showed that the second algorithm was better than the first algorithm in detecting various partial faults of the system. Therefore, the algorithm developed by using mathematical models and a RBF neural network may be used for the detection of partial faults of an air-conditioning system.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.37 no.4
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• pp.12-23
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• 2014

The O&M (Operation and Maintenance) phase of offshore plants with a long life cycle requires heavy charges and more efforts than the construction phase, and the occurrence of an accident of an offshore plant causes catastrophic damage. So previous studies have focused on the development of advanced maintenance system to avoid unexpected failures. Nowadays due to the emerging ICTs (Information Communication Technologies) and sensor technologies, it is possible to gather the status data of equipment and send health monitoring data to administrator of an offshore plant in a real time way, which leads to having much concern on the condition based maintenance policy. In this study, we have reviewed previous studies associated with CBM (Condition-Based Maintenance) of offshore plants, and introduced an algorithm predicting the next failure time of the compressor which is one of essential mechanical devices in LNG FPSO (Liquefied Natural Gas Floating Production Storage and Offloading vessel). To develop the algorithm, continuous time Markov model is applied based on gathered vibration data.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.32 no.4
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• pp.317-326
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• 2008

The main purpose of the present study is to perform shape optimizations of transonic compressor blade in order to enhance its performance. In this study, the Latin hypercube sampling of design of experiments and the weighted average surrogate model with the help of a gradient based optimization algorithm are used within design space by the lower and upper limits of each design variable and for finding optimum designs, respectively. 3-D Reynolds-averaged Navier-Stokes solver is used to evaluate the objective functions of adiabatic efficiency and pressure ratio. Six variables from lean and airfoil thickness profile are selected as design variables. The results show that the adiabatic efficiency is enhanced by 1.43% by efficiency optimization while the pressure ratio is increased very small, and pressure ratio is increased by 0.24% by pressure ratio optimization.

• 한국전산유체공학회:학술대회논문집
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• 1998.05a
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• pp.181-189
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• 1998

A numerical study based on the three-dimensional Reynolds averaged Navier-Stokes equations is presented to analyze the transonic flowfield through two-stage axial compressor. Explicit four-step Runge-Kutta scheme is used for solution algorithm, and local time step and implicit residual averaging are introduced for enhancing the convergency. Artificial dissipation model is adopted to assure the stability of solution. The solver is coupled with Baldwin-Lomax model to describe turbulence. To avoid calculating the unsteady flow, a mixing process is modeled at a station between rotating and stationary blade rows. Results show a variety of important physical phenomena. Comparison of the flowfields with and without tip clearance shows that the effect is considerable in this flowfield. Comparisons with experimental data carried out to validate the calculational results show reasonable agreements. Some remedies are also suggested to improve the revealed problems.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.11
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• pp.1639-1644
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• 2015

Auxiliary air compressor(ACM) applied to railroad cars is a device which controls amount of compressed air in order that pantographs can be mounted correctly on the roof of an electric train. Existing ACMs consist of dc motors and brushes wear out due to friction with a commutator. Therefore, continuous maintenance is required. However, three phase BLDC motors have higher power density compared to dc motors and the machine maintenance is not needed because electric commutation is possible. The three phase generally uses hall sensors to get position information and this enables the accurate control. This paper suggests an algorithm that compensates the errors occurred when the hall sensors have a breakdown for stable operation.

• Journal of the Korean Society for Precision Engineering
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• v.21 no.11
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• pp.125-129
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• 2004

For the diagnosis of compressor abnormal condition in air-conditioner, AE signal which is derived from wear condition, compressed air and assembly error is analyzed experimentally. The burst and continuous type AE signal occurred by metal contact and compressed air and AE raw signal of compressors were directly acquired in production line. After extracting samples according to waveforms, Early Life Test(ELT) is conducted and classified to normal and abnormal waveform. The efficient parameters of waveform pattern are investigated in time and frequency domain and the diagnosis algorithm of air-conditioner by Neural Network estimation is suggested.

• Proceedings of the SAREK Conference
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• 2005.11a
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• pp.469-473
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• 2005

Capacities of a tandom-type air-conditioner may be modulated by turning on/off multiple compressors and adjusting positions of a electronic expansion valve. In this study. control algorithms for compressors and a electronic expansion valve were developed by using fuzzy’ logics. There algorithms were implemented in a test lab and proved to be effective for the control of indoor air temperature and superheat temperature.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.35 no.7
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• pp.759-766
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• 2011

Recently, noise reduction in room air conditioners has been one of the important issues as well as cooling efficiency. The rotary compressor is the dominant noise source in an air conditioner. A number of studies have been conducted on reducing compressor noise through improving muffler and resonator design. However the noise from the accumulator, a noise delivering path between compressor and air conditioner, is not fully taken into consideration. The accumulator contains a large inner cavity, and usually generates additional resonance noise during operation. This paper aims to conduct an optimal design for reducing accumulator noise by maximizing the transmission loss within the target frequency range that represents high-order nonlinearity. Design of experiments and radial basis function neural network are used in the context of approximate meta-models, and genetic algorithm is used as an optimization tool.