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Determining Sampling Points Using Railway Track Structure Data Analysis

Tutkimustuotosvertaisarvioitu

Yksityiskohdat

AlkuperäiskieliEnglanti
OtsikkoInternational Conference on Information Technology in Geo-Engineering
AlaotsikkoProceedings of the 3rd International Conference (ICITG), Guimarães, Portugal
ToimittajatAntónio Gomes Correia, Joaquim Tinoco, Paulo Cortez, Luís Lamas
KustantajaSpringer, Cham
Sivut841-856
ISBN (elektroninen)978-3-030-32029-4
ISBN (painettu)978-3-030-32028-7
DOI - pysyväislinkit
TilaJulkaistu - 25 syyskuuta 2019
OKM-julkaisutyyppiA3 Kirjan tai muun kokoomateoksen osa
TapahtumaInternational Conference on Information Technology in Geo-Engineering -
Kesto: 1 tammikuuta 2000 → …

Julkaisusarja

NimiSpringer Series in Geomechanics and Geoengineering
ISSN (painettu)1866-8755
ISSN (elektroninen)1866-8763

Conference

ConferenceInternational Conference on Information Technology in Geo-Engineering
LyhennettäICITG
Ajanjakso1/01/00 → …

Tiivistelmä

In railway track asset management, limited funding is available to ensure safe and punctual train traffic on an aging rail network. Assessing railway structure problems, their severity and extent is a difficult and laborious task to which different methods have been applied. Further, determining problematic areas and identifying their rehabilitation needs are two separate operations. In this research, data mining and data analysis of railway track structure data was used to identify different types of track behavior and corresponding substructure conditions. A descriptive data mining method, Generalized Unary Hypothesis Automata (GUHA), was adopted. Soil samples were taken and tested on the basis of the conducted analyses. The purpose was to see whether deductions made from the data, concerning the condition of the track substructure, could be confirmed with soil sampling and related soil sample laboratory tests. The research was carried out in three parts. First, multiple data sources were used to comprise an initial data matrix, which was used in data mining and data analyses. After the analyses, fifty subballast and ten ballast sampling points were chosen according to the findings from data mining and data analysis, and samples were taken and tested. The last part of the research was to see how the laboratory test results corresponded with the analyses made from the data. The research showed that GUHA data mining and data analysis can be used to detect sections of track with problematic substructures, but further research is required to improve the initial data.

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