• Journal of the Korean Society for Railway
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• v.13 no.3
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• pp.304-308
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• 2010

This paper presents a methodology for identifying track irregularity using a wavelet transfer function. An equivalent wavelet SISO (single-input single-output) transfer function is defined by the measured track geometry and the acceleration data measured at a bogie of a train. All the measured data with various sampling frequencies were rearranged according to the constant 25cm reference recording distance of the track recording vehicle used in the field. Before applying the wavelet transform, measured data were regressed by eliminating those out of the range. The inverse wavelet transfer function is also formulated to estimate track geometry. The closeness of the estimated track geometry to the actual one is evaluated by the coherence function and also by FRF (frequency response function). A track irregularity index is defined by comparing the variance of the estimation error from the intact condition and that from the current condition. A simulation study has been carried out to examine the proposed algorithm.

• Journal of the Korean Society for Railway
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• v.12 no.4
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• pp.506-511
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• 2009

An algorithm for identifying track irregularities along the railway is presented. A baseline frequency-domain transfer function based on the equivalent SlSO(Single Input Single Output) model is defined at the intact condition between the measured track geometry of the ground displacement and the acceleration measured at a location in a train. The pre-defined transfer function at the intact condition is used inversely to predict track geometry in time with the currently measured acceleration at the same location in a train. The predicted track geometry is compared in time with that of the baseline values at the intact condition. The difference between them is calculated as an error in time and used to identify the track irregularities. An irregularity index is proposed as the ratio between the moving variance of the error at the current inspection and that at the intact condition. A 3D numerical simulation study has been carried out with a train model to verify the validity of the presented algorithm. In the analysis for the simulation, the track geometry has been considered as the displacement boundary condition varying in time.

• Journal of the Korean Society for Railway
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• v.19 no.4
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• pp.547-554
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• 2016

This study considered how to estimate the deterioration rate of the track quality index, which represents track geometric irregularity. Most existing studies have used a simple linear regression and regarded the slope of the regression equation as the progress rate. In this paper, we present a Bayesian approach to estimate the track irregularity progress. This Bayesian approach has many advantages, among which the biggest is that it can formally include the prior distribution of parameters which can be derived from historic data or from expert experiences; then, the rate can be expressed as a probability distribution. We investigated the possibility of applying the Bayesian method to the estimation of the deterioration rate by comparing our bayesian approach to the conventional linear regression approach.

• 한국방재학회:학술대회논문집
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• 2011.02a
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• pp.185-185
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• 2011

기존 장대레일 궤도의 안정성 평가는 궤도 매개변수에 대하여 고정된 안전측의 값을 사용하는 결정론적인 해석에 의존해서 평가되어져 왔다. 그러나 실제현장의 궤도조건은 많은 영향인자들에 의해 그 특성이 불확실하게 변하고 있다. 따라서 온도하중에 의한 궤도 좌굴에 영향을 미치는 궤도 구성인자들의 불확실성 및 임의성을 보다 합리적으로 고려하기 위해서 확률론적 기법을 적용하는 것이 필수적이다. 본 연구에서는 기존 본 연구진에 의해 개발된 장대레일 궤도의 좌굴확률 평가시스템을 이용하여 좌굴 취약도 곡선을 나타내었으며, 궤도 좌굴에 영향을 미치는 주요변수 중 하나인 도상횡저항력에 대한 영향을 분석하였다. 좌굴확률 평가시스템에서는 장대레일 궤도의 좌굴확률을 산정하기 위하여 구조물의 안정과 파괴를 판단할 수 있는 기준을 한계상태방정식으로 표현하고, 이 한계상태방정식으로부터 확률론적 기법 중 하나인 AFOSM(Advanced First Order Second Moment) 방법을 이용하여 파괴확률의 간접적인 지표인 신뢰도지수(${\beta}$)를 통해 좌굴확률을 계산한다. 한계상태방정식에서 구조물의 강도(보유성능)에 해당하는 부분은 궤도의 허용좌굴온도이고, 하중(요구성능)에 해당하는 부분은 레일온도하중으로써 현재 레일온도와 중립온도의 차로 반영된다. 허용좌굴온도 산정에 고려되는 주요변수는 곡선반경(Radius), 도상횡저항력(Lateral Ballast Resista nce), 연직도상강성(Vertical Ballast Stiffness), 궤도 틀림량(Misalignment), 틀림길이(Half Wave Length), 열차운행속도(Velocity)이다. 각 확률변수들이 갖는 확률분포는 모두 정규분포로 가정하였다. 궤도의 기하학적 특성은 곡선반경 5,000m에 대해 고려하였으며, 열차는 KTX의 제원을 사용하여 정지된 상태에서 고려하였다. 틀림량과 틀림길이는 이에 대한 통계적 특성자료가 부족하여 확률변수로 고려하지 않고 결정론적 값으로 취급하였다. 레일온도의 통계적 특성치는 본 연구진에 의해 구축된 기후요소 및 레일온도 DB를 근거로 결정하였으며, 중립온도는 선로관리지침에 따라 $25{\pm}3^{\circ}C$를 기준으로 결정하였다. 또한 도상횡저항력은 실측 데이터를 참고로 하여 평균값에서 10%의 변동량을 갖는 것으로 보고 통계적 특성치를 결정하였다. 도상횡저항력이 좌굴확률에 미치는 영향을 매우 큰 것을 알 수 있었으며, 레일온도 $60^{\circ}C$일 때 도상횡저항력이 증가하면서 감소되는 좌굴확률이 도상저항력이 커질수록 그 감소량이 작아지는 것을 알 수 있었다.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.25 no.4
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• pp.331-338
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• 2012

Irregularity data inspected by EM-120, an railway inspection system in Korea includes unavoidable incomplete and erratic information, so it is encountered lots of problem to analyse those data without appropriate pre-data-refining processes. In this research, for the efficient management and maintenance of railway system, characteristics and problems of the detected track irregularity data have been analyzed and efficient processing techniques were developed to solve the problems. The correlation between track irregularity and seasonal changes was conducted based on ARIMA model analysis. Finally, time series analysis was carried out by various forecasting model, such as regression, exponential smoothing and ARIMA model, to determine the appropriate optimal models for forecasting track irregularity progress.