Actual Data Analysis of Alignment Irregularity Growth and its Prediction Model

Kawaguchi, Akito; Miwa, Masashi; Terada, Kazuhiro

doi:10.2219/rtriqr.46.262

Cited by 36 publications

(26 citation statements)

References 1 publication

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“…For instance, the sleepers of a ballasted track settle down gradually over time [13]. The vertical rail irregularities resulting from ballast settlement ( Figure 2) are well known, and will be considered in this study.…”

Section: Types Of Track Irregularitiesmentioning

confidence: 99%

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A structural articulation method for assessing railway bridges subject to dynamic impact loading from track irregularities

Lilley

Franklin

2010

Vehicle System Dynamics

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This paper discusses the importance of track irregularities in railway bridge design, and presents a new technique for calculating the dynamic impact load induced by such irregularities: the structural articulation method. The properties of the combined bridge-suspension system are coupled through global mass, stiffness, and damping matrices. Under the proposed method, the true suspension system over a particular point on the bridge girder at time t is divided into equivalent suspension systems attributed to adjacent finite-element nodes of the bridge. The time-dependent effects of a moving mass are thereby included in the equation of motion.

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Section: Types Of Track Irregularitiesmentioning

confidence: 99%

“…This condensed stiffness matrix is given in Equation (13). There are no '0' elements in this matrix.…”

Section: Stiffness Matrixmentioning

confidence: 99%

A structural articulation method for assessing railway bridges subject to dynamic impact loading from track irregularities

Lilley

Franklin

2010

Vehicle System Dynamics

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“…19 Kawaguchi et al and Morimoto and Miwa at Railway Technical Research Institute in Japan have respectively developed degradation models which utilize standard deviations of track geometry measurements to predict standard deviations of track alignment and surface of 100m-long track sections. 20 Employing stochastic process theory, Iyengar and Jaiswal have analyzed track surface measurements obtained from two railway lines in India and concluded that track surface can be modeled as a stationary Gaussian stochastic process. 21 Alfelor et al have built a track degradation database storing track gauge restraints and track geometry parameters measured with Gage Restraint Measurement System, traffic loads, environment, track structural characteristics, and developed a track degradation analysis program which can formulate a one-to-one relationship between track degradation and a contributing parameter by employing least square linear regression.…”

Section: Introductionmentioning

confidence: 99%

A Novel Description Method for Track Irregularity Evolution

Xu¹,

Liu²,

Wang³

et al. 2011

IJCIS

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Track Irregularity has a significant influence on the safety of train operation. Due to the fact that the extremely large number of factors affect track irregularity， it is challenging to find a concise yet effective mathematical method to describe the evolution of track irregularity. In this paper, inspection data generated by GJ-4 track inspection cars from Jinan Railway Bureau in China were analyzed to identify the characteristics of track irregularity changes common to different mileage points. Based on these characteristics, a multi-stage linear fitting model to describe the pattern of track irregularity evolution over time was developed. The availability of new inspection data will make the model revise itself. In this sense, the model is a machine learning model. Finally, inspection data from the Beijing-Shanghai Railway Line (Jing-Hu Line) were used to verify the model.

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“…19 Kawaguchi et al and Morimoto and Miwa at Railway Technical Research Institute in Japan have respectively developed degradation models which utilize standard deviations of track geometry measurements to predict standard deviations of track alignment and surface of 100m-long track sections. 20 Employing stochastic process theory, Iyengar and Jaiswal have analyzed track surface measurements obtained from two railway lines in India and concluded that track surface can be modeled as a stationary Gaussian stochastic process. 21 System, traffic loads, environment, track structural characteristics, and developed a track degradation analysis program which can formulate a one-to-one relationship between track degradation and a contributing parameter by employing least square linear regression.…”

Section: Introductionmentioning

confidence: 99%