• Journal of computational fluids engineering
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• v.18 no.3
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• pp.51-59
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• 2013

A significant change in aerodynamic characteristics of wind turbine blade can occur by ice formed on the surface of the blade operated in cold climate. The ice accretion can result in performance loss, overloading due to delayed stall, and excessive vibration associated with mass imbalance. In this study, the impact of ice accretion on the aerodynamic characteristics of NREL 5MW wind turbine blade sections is examined by a CFD-based method. It is shown that the thickness of ice accretion increases from the root to the tip and the effects of icing conditions such as relative wind velocity play a significant role in the shape of ice accretion. In addition, the computational results are used to assess the degradation in the lift and drag coefficients of the blade sections.

• Transactions of the Society of Information Storage Systems
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• v.9 no.1
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• pp.5-9
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• 2013

Page-oriented holographic data storage (HDS) is very sensitive to the disturbances. However, vibration effect by disc imbalance can be ignored because data pages are recorded and retrieved with stop-go rotation. Therefore, just estimating de-track due to eccentricity of disc is enough to construct stable track servo system. In this paper, propose the spacing of track servo patterns optimization method using Least Mean Square (LMS) estimation algorithm. Through the patterns spacing optimization, storage density maximize can be achieved.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.82-84
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• 2021

Through the smart factory construction project, sensor data such as power, vibration, pressure, and temperature are collected from production facilities, and services such as predictive maintenance, defect prediction, and abnormality detection are developed through data analysis. In general, in the case of manufacturing data, because the imbalance between normal and abnormal data is extreme, an anomaly detection service is preferred. In this paper, FFT method is used to extract feature data of manufacturing data as a pre-stage of the anomaly detection service development. Using this method, we classified the produced products and confirmed results. In other words, after FFT of the representative pattern for each product, we verified whether product classification was possible or not, by calculating correlation coefficient.

• Journal of Wind Energy
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• v.13 no.3
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• pp.33-42
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• 2022

In this paper, a semi-supervised machine learning technique applied to actual field vibration data acquired from Jeju-do wind turbines for predictive diagnosis of abnormal conditions of offshore wind turbines is introduced. Semi-supervised machine learning, which combines un-supervised learning with supervised learning, can be used to perform anomaly detection in situations where sufficient fault data cannot be obtained. The signal processing results using the spectrogram of the original signal were shown, and external data were used to overcome the problem that disturbance reactions easily occurred due to the imbalance between the number of normal and abnormal data. Out of distribution (OOD), which uses external data, is a technology that is regarded as abnormal data that is unlikely to occur in reality, but we were able to use it by expanding it. By rearranging the distribution of data in this way, classification can be performed more robustly. Specifically, by observing the trends of the abnormal score and the change in the feature of the representation layer, continuous learning was performed through a mixture of existing and new data.

• Journal of KSNVE
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• v.8 no.5
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• pp.964-973
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• 1998

In this paper we propose a levitation and imbalance compensation controller design methodology of magnetic bearing system. In order to achieve levitation and elimination of unbalance vibartion in some operation speed we use the discrete-time Q-parameterization control. When rotor speed p = 0 there are no rotor unbalance, with frequency equals to the rotational speed. So in order to make levitatiom we choose the Q-parameterization controller free parameter Q such that the controller has poles on the unit circle at z = 1. However, when rotor speed p $\neq$ 0 there exist sinusoidal disturbance forces, with frequency equals to the rotational speed. So in order to achieve asymptotic rejection of these disturbance forces, the Q-parameterization controller free parameter Q is chosen such that the controller has poles on the unit circle at z = $exp^{ipTs}$ for a certain speed of rotation p ( $T_s$ is the sampling period). First, we introduce the experimental setup employed in this research. Second, we give a mathematical model for the magnetic bearing in difference equation form. Third, we explain the proposed discrete-time Q-parameterization controller design methodology. The controller free parameter Q is assumed to be a proper stable transfer function. Fourth, we show that the controller free parameter which satisfies the design objectives can be obtained by simply solving a set of linear equations rather than solving a complicated optimization problem. Finally, several simulation and experimental results are obtained to evaluate the proposed controller. The results obtained show the effectiveness of the proposed controller in eliminating the unbalance vibrations at the design speed of rotation.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.42 no.2
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• pp.134-143
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• 2014

A significant degradation in the aerodynamic performance of wind turbine system can occur by ice accretion on the surface of blades operated in cold climate. The ice accretion can result in performance loss, overloading due to delayed stall, excessive vibration associated with mass imbalance, ice shedding, instrumental measurement errors, and, in worst case, wind turbine system shutdown. In this study, the effects of ice accretions on the aerodynamic characteristics of wind turbine blade sections are investigated on the basis of modern CFD method. In addition, the computational results are used to predict the performance of three-dimensional wind turbine blade system through the blade element momentum method. It is shown that the thickness of ice accretion increases from the root to the tip and the effects of icing conditions such as relative wind velocity play significant role in the shape of ice accretion.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.38 no.10
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• pp.973-978
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• 2010

In this paper, we studied the shimmy phenomena of an aircraft nose landing gear considering free-play. Shimmy is a self-excited vibration in lateral and torsional directions of a landing gear during either the take-off or landing. This phenomena is caused by a couple of conditions such as low torsional stiffness of the strut, friction and free-play in the gear, wheel imbalance, or worn parts, and it may make an aircraft unstable. Free-play non-linearity is linearized by the described function for a stability analysis in a frequency domain, and time marching is performed using the fourth-order Runge-Kutta method. We performed the numerical simulation of the nose landing gear shimmy and investigated its linear and nonlinear characteristics. From the numerical results, we found limit-cycle-oscillations at the speed under linear shimmy speed for the case considering free-play and it can be concluded that the shimmy stability can be decreased by free-play.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.39 no.7
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• pp.605-611
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• 2011

Shimmy is a self-excited vibration in lateral and torsional directions of a landing gear during either the take-off or landing. It is caused by a couple of conditions such as a low torsional stiffness of the strut, a free-play in the landing gear, a wheel imbalance, or worn parts, and it may make the aircraft unstable. This study was performed for an analysis of the shimmy stability on a small aircraft. A nose landing gear was modeled as a linear system and characterized by state-equations which were used to analyze the stability both in the frequency and time-domain for predicting whether the shimmy occurs and investigating a good design range of the important parameters. The root-locus method and the 4th Runge-Kutta method were used for each analysis. Because the present system has a simple mechanism using a friction to reinforce the stability, the friction, a non-linear factor, was linearized by a describing function and considered in the analysis and observed the result of the instability reduction.

• Smart Structures and Systems
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• v.22 no.2
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• pp.185-192
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• 2018

Participants in the Asia Pacific Conference of the Prognostics and Health Management Society 2017 (PHMAP 2017) Data Challenge were given measured vibration signals from motor-driven gearboxes used in pulverizers. Using this information, participants were requested to predict failure dates and the faulty components. The measured signals were affected by significant noise and disturbance, as the pulverizers in the provided data worked under actual operating conditions. This paper thus presents a fault prediction method for a motor-driven gearbox in a pulverizer system that can perform under external noise and disturbance conditions. First, two fault features, an RMS value in the higher frequency zones (HRMS) and an amplitude of a period for high-speed shaft in the quefrency domain ($QA_{HSS}$), were extracted based on frequency analysis using the higher and lower sampling rate data. The two features were then applied to each pulverizer based on results of frequency responses to impact loadings. Then, a regression analysis was used to predict the failure date using the two extracted features. A weighted regression analysis was used to compensate for the imbalance of the features in the given period. In addition, the faulty components in the motor-driven gearboxes were predicted based on the modulated frequency components. The score predicted by the proposed approach was ranked first in the PHMAP 2017 Data Challenge.

• Tribology and Lubricants
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• v.36 no.5
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• pp.279-289
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• 2020

In this paper, a method is proposed for establishing an approximate prediction model of rotor-dynamics through modal testing. In particular, the proposed method is applicable to systems that cannot be established according to conventional methods owing to the absence of information regarding the dimensions and material of the rotor-bearing system. The proposed method is demonstrated by employing a motor dynamometer driven by a 1 MW class induction motor without dimension and material information. The proposed method comprises a total of seven steps, wherein an initial model is established by incorporating approximate dimensions and material information, and the model is improved on the basis of the natural frequency characteristics of the system. During model improvement, the modification factor is introduced for adjusting the elastic modulus and shear modulus of the system. Analysis of critical speed and imbalance response indicates that the separation margin is 67% and the maximum vibration amplitude is less than the amplitude limit of 0.032 mm under the API 611 standard, which means that the motor dynamometer can stably operate at a rated speed of 1800 rpm. Hence, the obtained results validate the feasibility of the proposed method. Furthermore, for broad usage, it is necessary to accordingly apply and validate the proposed method for various rotor-bearing systems.