• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2014.10a
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• pp.505-508
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• 2014

Transmission error (TE) is defined as "the angular difference between the ideal output shaft position and actual position". As TE is one of the major source of the noise and vibration of gears, it is originally studied with relation of the noise and vibration of the gears. However, recently, with the relation of mesh stiffness, TE has been studied for fault detection of spur gear sets. This paper presents a physics-based theory on fault diagnostics of a planetary gear using transmission error. After constructing the lumped parameter model using DAFUL, multi-body dynamics software, we developed a methodology to diagnose the faults of the planetary gear including phase calculation, signal processing. Using developed methodology, we could conclude that TE could be a good signal for fault diagnostics of a planetary gear.

• The Transactions of the Korean Institute of Power Electronics
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• v.3 no.1
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• pp.77-84
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• 1998

This paper describes a control system design for the transmission STATCOM by applying a no-linear state feedback, and the performance analysis of the control system by simulations and scaled-model experiments. A mathematical model for the STATCOM was derived using a 3-phase equivalent circuit and a perturbation state equation with respect to a typical operating point. A transfer function to describe the dynamics of STATCOM was derived by considering nonlinear state feedback. A controller design was completed by analyzing the feedback system stability with root locus method. The performance analysis of the conceived control system was verified by simulations with the EMTP and experiments with scaled model, assuming that the STATCOM is connected to an 154kV transmission system. The results show that the conceived control system has excellent performance to control the reactive power of the transmission system.

• Structural Engineering and Mechanics
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• v.90 no.1
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• pp.27-40
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• 2024

The prediction of VIV amplitude is essential for the design and fatigue life estimation of steel tubes in tubular transmission towers. Limited to costly and time-consuming traditional experimental and computational fluid dynamics (CFD) methods, a machine learning (ML)-based method is proposed to efficiently predict the VIV amplitude of steel tubes in transmission towers. Firstly, by introducing the first-order mode shape to the two-dimensional CFD method, a simplified response analysis method (SRAM) is presented to calculate the VIV amplitude of steel tubes in transmission towers, which enables to build a dataset for training ML models. Then, by taking mass ratio M^*, damping ratio ξ, and reduced velocity U^* as the input variables, a Kriging-based prediction method (KPM) is further proposed to estimate the VIV amplitude of steel tubes in transmission towers by combining the SRAM with the Kriging-based ML model. Finally, the feasibility and effectiveness of the proposed methods are demonstrated by using three full-scale steel tubes with C-shaped, Cross-shaped, and Flange-plate joints, respectively. The results show that the SRAM can reasonably calculate the VIV amplitude, in which the relative errors of VIV maximum amplitude in three examples are less than 6%. Meanwhile, the KPM can well predict the VIV amplitude of steel tubes in transmission towers within the studied range of M^*, ξ and U^*. Particularly, the KPM presents an excellent capability in estimating the VIV maximum amplitude by using the reduced damping parameter S_G.

• Journal of Electrical Engineering and Technology
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• v.10 no.2
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• pp.625-633
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• 2015

The effect of altitude on thermal conduction, surface temperature, and thermal radiation of partial arc was investigated on the basis of molecular gas dynamics to facilitate a deep understanding of the pollution surface discharge mechanism. The DC flashover model was consequently modified at high altitude. The validity of the modified DC flashover model proposed in this paper was proven through a comparison with the results of high-altitude simulation experiments and earlier models. Moreover, the modified model was found to be better than the earlier modified models in terms of forecasting the flashover voltage. Findings indicated that both the thermal conduction coefficient and the surface thermodynamics temperature of partial arc had a linear decrease tendency with the altitude increasing from 0 m to 3000 m, both of which dropped by approximately 30% and 3.6%, respectively. Meanwhile, the heat conduction and the heat radiation of partial arc both had a similar linear decrease of approximately 15%. The maximum error of DC pollution flashover voltage between the calculation value according to the modified model and the experimental value was within 6.6%, and the pollution flashover voltage exhibited a parabola downtrend with increasing of pollution.

• Journal of the Korean Institute of Intelligent Systems
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• v.8 no.2
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• pp.117-127
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• 1998

Power systems have uncertain dynamics due to a variety of effects such as lightning, severe storms and equipment failures. The variation of the effective reactance of a transmission line due to a fault is an example of uncertainty in power system dynamics. Hence, a robust controller to cope with these uncertainties is needed. Recently, fuzzy controllers are becoming quite popular for robust control due to its potential of dealing with uncertain systems. Thus in this paper we design an adaptive fuzzy controller based on an input-output linearization approach for the transient stabilization and voltage regulation of a power system under a sudden fault. Also this paper proposes a fuzzy system that estimates the upper bound of uncertain term in the system dynamics to guarantee the Lyapunov stability. Simulation results show that good performance is achieved by the proposed controller.

• Journal of applied mathematics & informatics
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• v.39 no.1_2
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• pp.197-214
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• 2021

In this paper, we have studied dynamics of fractional order mathematical model of malaria transmission for two groups of human population say semi-immune and non-immune along with growing stages of mosquito vector. The present fractional order mathematical model is the extension of integer order mathematical model proposed by Ousmane Koutou et al. For this study, Atangana-Baleanu fractional order derivative in Caputo sense has been implemented. In the view of memory effect of fractional derivative, this model has been found more realistic than integer order model of malaria and helps to understand dynamical behaviour of malaria epidemic in depth. We have analysed the proposed model for two precisely defined set of parameters and initial value conditions. The uniqueness and existence of present model has been proved by Lipschitz conditions and fixed point theorem. Generalised Euler method is used to analyse numerical results. It is observed that this model is more dynamic as we have considered all classes of human population and mosquito vector to analyse the dynamics of malaria.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.432-437
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• 1998

Power systems have uncertain dynamics due to a variety of effects such as lightning, severe storms and equipment failures. The variation of the effective reactance of a transmission line due to a fault is an example of uncertainty in power system dynamics. Hence, a robust controller to cope with these uncertainties is needed. Recently fuzzy controllers have become quite popular for robust control due to its capability of dealing with unstructured uncertainty. Thus in this paper we design an adaptive fuzzy controller using an input-output linearization approach for the transient stabilization and voltage regulation of a power system under a sudden fault. Simulation results show that satisfactory performance is achieved by the proposed controller.

• Journal of Mechanical Science and Technology
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• v.15 no.12
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• pp.1623-1629
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• 2001

This parer presents a CVT line pressure control strategy for the increased shift speed. Firstly, an algorithm to increase the CVT shift speed is suggested based on a modified CVT shift dynamics and shift speed maps are constructed. In addition, simplified dynamic models of the line pressure and the ratio control valve are derived by considering the CVT shift dynamics, and low level control algorithms for the ratio and the line pressure control are proposed. Using the shift speed maps and the simplified dynamic models of the CVT system, shift performance is investigated. It is found from the experimental and simulation results that improved shift speed can be achieved by increasing the lilly pressure.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.20 no.1
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• pp.284-294
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• 1996

In this paper, dynamic characteristics of an AT clutch system were investigated considering the dynamics of check ball and hydraulic control valves. Dynamic model of a pressure control solenoid valve (PCSV) was obtained by Bondgraph and permeance method. Also, the clutch piston and check ball dynamics were modeled by considering the effect of centrifugal force of the oil entrapped in the clutch chamber. In order to validate the dynamic models obtained, plunger displacement of PCSV and pressure response of the clutch supply lines were compared with the available experimental data, which were in good accordance with the numerical results. Using the dynamic model of the clutch system, simulations were performed to investigate the effect of the rotational speed on the response of clutch cylinder pressure, clutch piston and check ball displacement, and oil flow rate into the cylinder and flow rate out of the check valve.

• Journal of Communications and Networks
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• v.5 no.1
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• pp.65-72
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• 2003

Internet roundtrip delay/time (RTT) prediction plays an important role in detecting packet losses in reliable transport protocols for traditional web applications and determining proper transmission rates in many rate-based TCP-friendly protocols for Internet-based real-time applications. The widely adopted autoregressive and moving average (ARMA) model with fixed-parameters is shown to be insufficient for all scenarios due to its intrinsic limitation that it filters out all high-frequency components of RTT dynamics. In this paper, we introduce a novel parameter-varying RTT model for Internet roundtrip time prediction based on the information theory and the maximum entropy principle (MEP). Since the coefficients of the proposed RTT model are updated dynamically, the model is adaptive and it tracks RTT dynamics rapidly. The results of our experiments show that the MEP algorithm works better than the ARMA method in both RTT prediction and RTO estimation.