• Tribology and Lubricants
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• 제27권2호
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• pp.57-64
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• 2011

Hybrid air-foil magnetic bearing integrates two oil free bearing technologies synergetically to adopt the strengths of two bearings with minimizing their weaknesses. This paper presents bending mode vibration control of a flexible shaft supported by the hybrid air-foil magnetic bearing. An experiment set-up of a flexible shaft supported by the hybrid air-foil magnetic bearing is built. In order to verify the effectiveness of the hybrid bearing, unbalance responses of the flexible shaft supported by three different bearings: air-foil, magnetic and hybrid bearings are compared. Effect of load sharing between air-foil and magnetic bearings are investigated through changing the control gain and the rotor center position of magnetic bearing. The experimental results shows that the hybrid bearing can control the bending mode vibration of the flexible shaft effectively and an optimal performance can be achieved with an appropriate load sharing between the air-foil and the magnetic bearings.

• 제어로봇시스템학회논문지
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• 제17권8호
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• pp.833-842
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• 2011

The objectives of this research are development of guidance, navigation and control system for RUAV on virtual instrumentation and real flight test. For this research, the system is divided to DAQ (data acquisition) section, actuator section and controller section. And the hardware and software on each sections are realized on LabVIEW base. Waypoint guidance and control of auto flight are realized using PID gain tuning and waypoint vector tracking guidance algorism. For safe flight test, auto/manual switching module isolated from FCS (Flight Control System) is developed. By using the switch module, swift mode change was achieved during emergency flight case. Consequently, a meter level error of flight performance is achieved.

• 유체기계공업학회:학술대회논문집
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• 유체기계공업학회 2000년도 유체기계 연구개발 발표회 논문집
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• pp.163-168
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• 2000

A method to search the design parameters for optimum stage matching has been used based on a 1-D mathematical model of a compressor, which uses the data obtained from the preliminary test to identify the design parameters. This methodology was applied with a two-stage axial compressor, which was originally designed for a helicopter gas turbine engine. After Identifying design parameters using preliminary test data, an optimization process has been employed to achieve the best matching between the stages (i.e., maximum efficiency of the compressor at its operation modes within a given range of the rotor speed under given restrictions for required stall margins and mass flow). 3-D flow calculations have been performed to confirm the usefulness of the corrections based on 1-D mathematical model. Calculational results agree well with the experimental data in view of the performance characteristics. Some promising results were produced through the methodology proposed in this paper in conjunction with flow calculations.

• 항공우주기술
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• 제3권2호
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• pp.248-255
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• 2004

본 논문에서는 반응면 기법(response surface method)과 2차원 Navier-Stokes 방정식 해법을 이용하여 에어포일을 설계하였다. 수치 실험점들은 D-optimal 방법을 기반으로 선정하였으며 반응면 함수는 JMP를 이용하여 2차의 함수로 구성하였다. 설계기법의 검증은 NACA 64621 에어포일을 기저로 하여 Bell 에어포일의 공력특성을 갖도록 역설계하여 수행하였다. 설계기법은 스마트 무인기의 장기체공 능력을 위한 에어포일과 무인기용 로터에 적합한 저 Reynolds 에어포일 설계에 적용하였으며 제약조건을 만족하는 우수한 공력특성의 에어포일을 획득할 수 있었다.

• 한국전산유체공학회지
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• 제17권1호
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• pp.54-60
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• 2012

Transition prediction results are validated with experimental data obtained from a transonic wind tunnel for the KU109C airfoil. A Reynolds-Averaged Navier-Stokes code is simultaneously coupled with the transition transport model of Langtry and Menter and applied to the numerical prediction of aerodynamic performance of the KU109C airfoil. Drag coefficients from the experiment are better correlated to the numerical prediction results using a transition transport model rather than the fully turbulent simulation results. Maximum lift coefficient and drag divergence at the zero-lift condition with Mach number are investigated. Through the present validation procedure, the accuracy and usefulness of both the experiment and the numerical prediction are assessed.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2001년도 추계학술대회논문집B
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• pp.30-35
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• 2001

To get higher efficiency of gas turbine, The designer should have more higher turbine inlet temperature (TIT). Today, modem gas turbine having sophisticated cooling scheme has TIT above $1,700^{\circ}C$. In the korea, many gas turbine having TIT above $1,300^{\circ}C$ was imported and being operated, but the gas with high TIT above $1,300^{\circ}C$ in the turbine will give damage to liner of combustor, and blade of turbine and etc. So frequently maintenance for parts enduring high temperature was performed. In this study, the heat transfer analysis of cooling air in the internal cooling channel (network analysis) and temperature analysis of the blade (Finite Element Analysis) in the first stage rotor was conducted for development of the optimal cooling passage design procedure. The results of network analysis and FEM analysis of blade show that the high temperature spot are occured at the leading edge, trailing edge near tip, and platform. so to get more reliable performance of gas turbine, the more efficient cooling method should be applied at the leading edge and tip section. and the thermal barrier coating on the blade surface has important role in cooling blade.

• Journal of Mechanical Science and Technology
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• 제17권12호
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• pp.1844-1854
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• 2003

This paper discusses details of modeling and robust control of an AMB (active magnetic bearing) spindle, and part I presents a modeling and validation process of the AMB spindle. There are many components in AMB spindle : electromagnetic actuator, sensor, rotor, power amplifier and digital controller. If each component is carefully modeled and evaluated, the components have tight structured uncertainty bounds and achievable performance of the system increases. However, since some unknown dynamics may exist and the augmented plant could show some discrepancy with the real plant, the validation of the augmented plant is needed through measuring overall frequency responses of the actual plant. In addition, it is necessary to combine several components and identify them with a reduced order model. First, all components of the AMB spindle are carefully modeled and identified based on experimental data, which also render valuable information in quantifying structured uncertainties. Since sensors, power amplifiers and discretization dynamics can be considered as time delay components, such dynamics are combined and identified with a reduced order. Then, frequency responses of the open-loop plant are measured through closed-loop experiments to validate the augmented plant. The whole modeling process gives an accurate nominal model of a low order for the robust control design.

• 대한기계학회논문집B
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• 제24권3호
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• pp.325-337
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• 2000

A study was done on the numerical and experimental analyses of the aerodynamic characteristics of a counter rotating axial fan. The numerical analysis uses the frequency domain panel method developed for the aerodynamic analysis of interacting rotating systems, which is based on the unsteady lifting surface panel method. Each stage of interaction involves the solution of an isolated rotor, the interaction being done through the Fourier transform of the induced velocity field. Numerical results showed good agreements with other experimental data for single and counter rotating propeller systems. And they were compared with the experimental results of the counter rotating axial fan studied in the present paper. The performance test was carried out based on the Korean Standard (KS B 6311). It was focused on the relative efficiency increase of a counter rotating system for a single rotating one, and effects of the axial distance between the front and rear rotors on overall fan performances were investigated. As a result, it was shown that the counter rotating axial fan has the efficiency 14% higher than the single rotating one at peak efficiency points.

• Wind and Structures
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• 제19권2호
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• pp.199-217
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• 2014

Reported experimental and computational fluid dynamic (CFD) studies have demonstrated significant power augmentation of diffuser shrouded horizontal axis micro wind turbine compared to bare turbine. These studies also found the degree of augmentation is strongly dependent on the shape and geometry of the diffuser such as length and expansion angle. However study flow field over the rotor blades in shrouded turbine has not received much attention. In this paper, CFD simulations of an experimental diffuser shrouded micro wind turbine have been carried out with the aim to understand the mechanisms underpinning the power augmentation phenomenon. The simulations provide insight of the flow field over the blades of bare wind turbine and of shrouded one elucidating the augmentation mechanisms. From the analysis, sub-atmospheric back pressure leading to velocity augmentation at the inlet of diffuser and lowering the static pressure on blade suction sides have been identified as th dominant mechanisms driving the power augmentation. And effective augmentation was achieved for ${\lambda}$ above certain value. For the case turbine it is ${\lambda}$ greater than ${\approx}2$.

• Smart Structures and Systems
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• 제22권2호
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• pp.175-183
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• 2018

Time-series data often contain one of the most valuable pieces of information in many fields including manufacturing. Because time-series data are relatively cheap to acquire, they (e.g., vibration signals) have become a crucial part of big data even in manufacturing shop floors. Recently, deep-learning models have shown state-of-art performance for analyzing big data because of their sophisticated structures and considerable computational power. Traditional models for a machinery-monitoring system have highly relied on features selected by human experts. In addition, the representational power of such models fails as the data distribution becomes complicated. On the other hand, deep-learning models automatically select highly abstracted features during the optimization process, and their representational power is better than that of traditional neural network models. However, the applicability of deep-learning models to the field of prognostics and health management (PHM) has not been well investigated yet. This study integrates the "residual fitting" mechanism inherently embedded in the wavelet transform into the convolutional neural network deep-learning structure. As a result, the architecture combines a signal smoother and classification procedures into a single model. Validation results from rotor vibration data demonstrate that our model outperforms all other off-the-shelf feature-based models.