scholarly journals Dimensioning windows for railway infrastructure maintenance: Cost efficiency versus traffic impact

2016 ◽  
Vol 6 (1) ◽  
pp. 32-47 ◽  
Author(s):  
Tomas Lidén ◽  
Martin Joborn
Keyword(s):  
Cost Efficiency ◽  
Maintenance Cost ◽  
Railway Infrastructure ◽  
Traffic Impact ◽  
Infrastructure Maintenance

Diagnostics of Track Infrastructure as Part of the Digitisation of Russian Railways

2020 ◽  
Vol 64 (188) ◽  
pp. 149-160
Author(s):  
Janusz Poliński
Keyword(s):  
Diagnostic Tools ◽  
Gradual Transition ◽  
Technical Diagnostics ◽  
Strategic Development ◽  
Railway Infrastructure ◽  
Monitoring And Forecasting ◽  
Infrastructure Maintenance ◽  
Result Analysis ◽  
Railway Maintenance ◽  
Condition Diagnosis

Technical diagnostics is an integral part of the railway maintenance process. Through timely maintenance, in addition to ensuring the safety, functional and technical reliability of the infrastructure, maintenance costs are reduced and downtime losses, due to failures or premature repair requests, are eliminated or reduced. The track infrastructure diagnostic tools have evolved. This is related to, among others, the miniaturisation of instruments, reading accuracy during motion, as well as upgraded measurement automation and result analysis. Currently, data obtained from multifunctional diagnostic tools is the basis for the developed Russian railway infrastructure maintenance and operation digital model. The strategic development of mobile diagnostic labs is the gradual transition to solutions with advanced digital analysis, supported by artificial intelligence, monitoring and forecasting. The article presents the development of mobile labs for the railroad infrastructure condition diagnosis up to the current solutions, in which measurements take place without human intervention and the obtained information is transmitted in real time to the analysis and decision centres. Keywords: rail transport, measuring wagons, digitisation of railways, Russian railways

scholarly journals Research on the application of BDS/GIS/RS technology in the high speed railway infrastructure maintenance

2021 ◽  
Vol 783 (1) ◽  
pp. 012168
Author(s):  
Jianfeng Yang ◽  
Xuejiao Bai ◽  
Zhuoxin Zhang ◽  
Meihao Yang ◽  
Peifen Pan ◽  
...  
Keyword(s):  
High Speed ◽  
High Speed Railway ◽  
Railway Infrastructure ◽  
Infrastructure Maintenance

scholarly journals Model for Railway Infrastructure Management Organization

1970 ◽  
Vol 24 (2) ◽  
pp. 99-107
Author(s):  
Gordan Stojić ◽  
Slavko Vesković ◽  
Ilija Tanackov ◽  
Sanjin Milinković
Keyword(s):  
Hybrid Model ◽  
Infrastructure Management ◽  
Train Station ◽  
Railway Company ◽  
Railway Systems ◽  
Railway Traffic ◽  
Railway Infrastructure ◽  
Rail Infrastructure ◽  
Management Modes ◽  
Infrastructure Maintenance

The provision of appropriate quality rail services has an important role in terms of railway infrastructure: quality of infrastructure maintenance, regulation of railway traffic, line capacity, speed, safety, train station organization, the allowable lines load and other infrastructure parameters.The analysis of experiences in transforming the railway systems points to the conclusion that there is no unique solution in terms of choice for institutional rail infrastructure management modes, although more than nineteen years have passed from the beginning of the implementation of the Directive 91/440/EEC. Depending on the approach to the process of restructuring the national railway company, adopted regulations and caution in its implementation, the existence or absence of a clearly defined transport strategy, the willingness to liberalize the transport market, there are several different ways for institutional management of railway infrastructure.A hybrid model for selection of modes of institutional rail infrastructure management was developed based on the theory of artificial intelligence, theory of fuzzy sets and theory of multicriteria optimization.KEY WORDSmanagement, railway infrastructure, organizational structure, hybrid model

Application of C4.5 Algorithm in Evaluation of Railway Large Maintenance Machinery Construction

2014 ◽  
Vol 496-500 ◽  
pp. 1770-1773
Author(s):  
Wei Qiao Zhu ◽  
Tian Yun Shi
Keyword(s):  
Decision Tree ◽  
Training Sample ◽  
Important Research ◽  
Machinery Construction ◽  
Railway Infrastructure ◽  
Tree Modeling ◽  
Sample Data ◽  
C4.5 Algorithm ◽  
Evaluation Decision ◽  
Infrastructure Maintenance

With improvement of the level of modernization and mechanization of railway infrastructure maintenance, Railway large maintenance machinery (RLMM) is considered to be one of the main equipment. We have accumulated large amounts of RLMM construction data. How to mine valuable information from these data has become an important research subject. The C4.5 algorithm of decision tree is a useful method of data mining and classification. The paper solves evaluation of RLMM construction problem based on the C4.5 algorithm. By means of extracting the attribute with maximum gain ratio as the root node of the decision tree from training sample data, the evaluation decision tree was constructed. The decision tree modeling of evaluation of RLMM construction was gained by the post-pruning approach. The experimental results and analysis show that this model has high precision and credibility.

scholarly journals Railway Vehicle Wheel Flat Detection with Multiple Records Using Spectral Kurtosis Analysis

2021 ◽  
Vol 11 (9) ◽  
pp. 4002
Author(s):  
Araliya Mosleh ◽  
Pedro Aires Montenegro ◽  
Pedro Alves Costa ◽  
Rui Calçada
Keyword(s):  
Detection System ◽  
Railway Vehicle ◽  
Optimal Position ◽  
Maintenance Costs ◽  
Spectral Kurtosis ◽  
Railway Systems ◽  
Railway Infrastructure ◽  
Wheel Flat ◽  
Infrastructure Maintenance ◽  
Envelope Spectrum

The gradual deterioration of train wheels can increase the risk of failure and lead to a higher rate of track deterioration, resulting in less reliable railway systems with higher maintenance costs. Early detection of potential wheel damages allows railway infrastructure managers to control railway operators, leading to lower infrastructure maintenance costs. This study focuses on identifying the type of sensors that can be adopted in a wayside monitoring system for wheel flat detection, as well as their optimal position. The study relies on a 3D numerical simulation of the train-track dynamic response to the presence of wheel flats. The shear and acceleration measurement points were defined in order to examine the sensitivity of the layout schemes not only to the type of sensors (strain gauge and accelerometer) but also to the position where they are installed. By considering the shear and accelerations evaluated in 19 positions of the track as inputs, the wheel flat was identified by the envelope spectrum approach using spectral kurtosis analysis. The influence of the type of sensors and their location on the accuracy of the wheel flat detection system is analyzed. Two types of trains were considered, namely the Alfa Pendular passenger vehicle and a freight wagon.

Sign in / Sign up

Export Citation Format

Share Document