Identification of Light Rail Track Geometry for Tram Running

2016 ◽  
Author(s):  
J. Kominowski ◽  
B. Firlik
Keyword(s):  
Light Rail ◽  
Track Geometry ◽  
Rail Track

Application of Artificial Neural Networks in Predicting the Degradation of Tram Tracks Using Maintenance Data

2020 ◽  
pp. 845-864
Author(s):  
Sara Moridpour ◽  
Ehsan Mazloumi ◽  
Reyhaneh Hesami
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Asset Management ◽  
Management Strategies ◽  
Operating Cost ◽  
Light Rail ◽  
Ann Model ◽  
Track Geometry ◽  
Artificial Neural ◽  
And Performance

The increase in number of passengers and tramcars will wear down existing rail structures faster. This is forcing the rail infrastructure asset owners to incorporate asset management strategies to reduce total operating cost of maintenance whilst improving safety and performance. Analysing track geometry defects is critical to plan a proactive maintenance strategy in short and long term. Repairing and maintaining the correctly selected tram tracks can effectively reduce the cost of maintenance operations. The main contribution of this chapter is to explore the factors influencing the degradation of tram tracks (light rail tracks) using existing geometric data, inspection data, load data and repair data. This chapter also presents an Artificial Neural Networks (ANN) model to predict the degradation of tram tracks. Predicting the degradation of tram tracks will assist in understanding the maintenance needs of tram system and reduce the operating costs of the system.

scholarly journals APPLICATION OF RAIL TRACK GEOMETRY MEASURING TROLLEYS FOR GEOREFERENCING OF UAV IMAGES

2021 ◽  
Vol XLIII-B2-2021 ◽  
pp. 101-107
Author(s):  
V. V. Shcherbakov ◽  
M. A. Altyntsev ◽  
M. A. Altyntseva
Keyword(s):  
Low Cost ◽  
Control Point ◽  
Point Clouds ◽  
Aerial Survey ◽  
Control Points ◽  
Data Types ◽  
Track Geometry ◽  
Rail Track ◽  
Uav Images ◽  
The Cost

Abstract. Rail track geometry measuring trolleys are widely used in the railway industry. They can collect information about the state of rails with high accuracy. Nowadays there are a lot of trolleys. Principles of measurements in different trolleys may vary greatly. The trolleys that can use the absolute method of measuring coordinates have advantages. Coordinates of rails and rail track axis can be used as control points for georeferencing of any other surveying data. UAV images are one of these data types. In railways aerial survey using UAVs is mostly used for mapping, gathering data for creation of profiles and some other measurements. UAVs allow reducing the volume of field surveying works. The cost of UAVs is very different. Application of low-cost UAVs imposes increased requirements to distribution of control points. As distribution of control points taken from a trolley trajectory is poor, the issue of such control point application emerges. The study of opportunity to use the trolley trajectory for georeferencing of UAV images is carried out. Accuracy estimation of generating photogrammetric models and image-based point clouds using control point coordinates measured with the trolley is given. Accuracy of measuring obstruction clearances with the help of image-based point clouds is estimated.

scholarly journals A Case Study of BIM Implementation in Rail Track Rehabilitation

2019 ◽  
Vol 4 (1) ◽  
pp. 8 ◽  
Author(s):  
José Neves ◽  
Zita Sampaio ◽  
Manuel Vilela
Keyword(s):  
Three Dimensional ◽  
Parametric Representation ◽  
3D Models ◽  
Information Modeling ◽  
Planning And Scheduling ◽  
Track Geometry ◽  
Rail Track ◽  
Building Information ◽  
Types Of Information

Building Information Modeling (BIM) is an Industry 4.0 methodology that is increasingly used in the domain of Architecture, Engineering, and Construction (AEC). BIM emerges as a new methodology, one that is more collaborative and based on parametric three-Dimensional (3D) models, centralizing different types of information of a geometric, physical, and economic nature. The purpose of this paper is to analyze the application of the BIM methodology to a rail track rehabilitation case study using a geotextile and geogrid in the ballast layer base. The creation of the 3D and 4D BIM models was performed using various BIM-based tools, which made it possible to achieve the spatial and parametric representation of the rail track and the simulation of the main construction tasks. A new BIM object pertaining to the rail track was created. This paper describes the procedures applied in achieving the BIM models, the limitations involved, and the interoperability between the BIM tools. Additionally, the potential for information extraction with respect to the infrastructure design, construction, and operation, e.g., planning and scheduling, quantities, graphic outputs, and track geometry quality, was demonstrated. It was concluded that the BIM methodology was viable and could be implemented with benefits, despite certain difficulties and limitations, which emphasize the need for further developments.

DEFLECTION PROFILE OF A NEW LIGHT RAIL TRACK SYSTEM.

1996 ◽  
Vol 117 (4) ◽  
pp. 272-277 ◽  
Author(s):  
H AL NAGEIM ◽  
F MOHAMMAD ◽  
L LESLEY ◽  
Keyword(s):  
Light Rail ◽  
Rail Track ◽  
Track System

scholarly journals Hybrid Rail Track Quality Analysis using Nonlinear Dimension Reduction Technique with Machine Learning

2021 ◽  
Author(s):  
Ahmed Lasisi ◽  
Nii Attoh-Okine
Keyword(s):  
Dimension Reduction ◽  
Poor Performance ◽  
Quality Analysis ◽  
Track Geometry ◽  
Rail Track ◽  
Nonlinear Dimension Reduction ◽  
Study Results ◽  
Nonlinear Dimension ◽  
Validation Set ◽  
Track Quality

Track Geometry parameters from rail track inspection are regulated within unique safety limits for different track classes. This paper focuses on developing an index that combines safety and track quality because of the inefficiency of having corrective maintenance activities between routine maintenance cycles when federal geometry limits are violated. This combination is achievable by summarizing multivariate track geometry parameters, as an improvement to previous linear approaches to address the problem of inefficient track geometry maintenance programs. The use of nonlinear dimension reduction (T-Stochastic Neighbor Embedding-T-SNE) for Hybrid Track Quality Index development, and the influence of time-based parameters on track quality is evaluated in this study. Results show that probability of geometry defects are correlated with principal components but T-SNE had the best prediction on train-test splits despite its poor performance on a blind validation set. The absence of observable correlation between track geometry and acceleration data calls for further investigation.

Quantification of Rail Displacements Under Light Rail Transit Field Loading Conditions

2017 ◽  
Author(s):  
Alvaro E. Canga Ruiz ◽  
Matthew V. Csenge ◽  
J. Riley Edwards ◽  
Yu Qian ◽  
Marcus S. Dersch
Keyword(s):  
Field Data ◽  
Past Research ◽  
Field Analysis ◽  
Light Rail ◽  
Rail Transit ◽  
Primary Role ◽  
Loading Conditions ◽  
Light Rail Transit ◽  
Transit System ◽  
Track Geometry

While timber crossties are widely used in North America, the popularity of concrete crossties has increased significantly in recent years. Concrete crossties require the use of premium elastic fastening systems to have a proper and stable system. The primary role of fastening system is to attach the rail to its support preserving track geometry. For this reason, past research has focused on its development and behavior. Even though a large amount of research has been conducted on heavy-haul freight railroad systems, little work has been conducted to focus on rail transit systems. Therefore, a field analysis of the behavior of fastening systems under rail transit system loading conditions has been executed, focusing on light rail transit loading conditions. To perform this study, revenue service field data were collected on a light rail transit system. The instrumentation used and how it was installed on site are described in this paper. The critical quantitative metric discussed in this study is the relative displacement of the rail with respect to the concrete crosstie. Analyzing vertical and horizontal displacements, as well as rotation, the performance of the fastening system can be evaluated. For this purpose, different sites on the same rail system were selected for study, comparing both curve and tangent track geometry. In addition to this, the movement of the rail under every axle of the light rail vehicle has been studied in detail. In summary, an analysis of how the rail performs in terms of displacement under light rail transit loading conditions has been completed. Based on field data, the analysis allows the reader to understand how the rail displaces under the given loads when it is installed in a ballasted concrete crosstie track and restrained by elastic fastening systems.

scholarly journals Rail Degradation Prediction Models for Tram System: Melbourne Case Study

2018 ◽  
Vol 2018 ◽  
pp. 1-8 ◽  
Author(s):  
Amir Falamarzi ◽  
Sara Moridpour ◽  
Majidreza Nazem ◽  
Reyhaneh Hesami
Keyword(s):  
Prediction Models ◽  
Model Development ◽  
Light Rail ◽  
Data Sets ◽  
Ann Model ◽  
Track Geometry ◽  
Degradation Data ◽  
High Acceleration ◽  
Acceleration And Deceleration ◽  
Ann Models

Tram is classified as a light rail mode of transportation. Tram tracks experience high acceleration and deceleration forces of locomotives and wagons within their service life and also share their route with other vehicles. This results in higher rates of degradation in tram tracks compared to the degradation rate in heavy rail tracks. In this research, gauge deviation is employed as a representative of track geometry irregularities for the predication of the tram track degradation. Data sets used in this research were sourced from Melbourne’s tram system. For model development, the data of approximately 250 km of tram tracks are used. Two different models including a regression model and an Artificial Neural Networks (ANN) model have been applied for predicting tram track gauge deviation. According to the results, the performances of the regression models are similar to the ANN models. The determination coefficients of the developed models are above 0.7.

Sign in / Sign up

Export Citation Format

Share Document