{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/122064"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/122064","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Development of relationships and trending methodologies for railroad track component and geometry data","abstract":"Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2024-03-01 without embargo terms","abstract_html":"Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2024-03-01 without embargo terms","abstract_has_math":false,"creators":["Morgado Bilheri T Carvalho, Arthur"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"M.S.","degree_level":"Thesis","degree_discipline":"Civil Engineering","degree_department":null,"school":null,"contributors":["Edwards, John Riley"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2023,"date_issued":"2023-12","date_published":"2023-12","updated_at":"2026-07-22T22:25:00Z","subjects":["Railway","Track","Geometry","Degradation"],"languages":["en","eng"],"rights":["Copyright 2023 Arthur Morgado Bilheri T Carvalho"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/2142/122064","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Edwards, John Riley"]},{"key":"dc:creator","label":"Author","values":["Morgado Bilheri T Carvalho, Arthur"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2023-12","2023-12-07"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Civil Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["M.S."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Railway","Track","Geometry","Degradation"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en","eng"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2023 Arthur Morgado Bilheri T Carvalho"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://hdl.handle.net/2142/122064"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2024-03-01 without embargo terms","The student, Arthur Morgado Bilheri T Carvalho, accepted the attached license on 2023-12-06 at 09:31.","The student, Arthur Morgado Bilheri T Carvalho, submitted this Thesis for approval on 2023-12-06 at 09:32.","This Thesis was approved for publication on 2023-12-07 at 16:27.","DSpace SAF Submission Ingestion Package generated from Vireo submission #20141 on 2024-03-01 at 13:15:27","The safe and efficient movement of trains requires periodic inspection of the geometry of the track system and health of its components. Railroads have used laser-based track geometry testing to comply with regulatory requirements and internal business practices for over 30 years. More recently, these systems have been supplemented by new technologies capable of inspecting many other attributes of the track including subgrade condition, track component health, and ballast profile. Computational advances including machine vision and artificial intelligence, and the application of big data, have drastically increased the value that can be derived from the ever-growing track health dataset. In this thesis, I present a method to manage the flow of data in a railroad, starting from field data collection to multi-year capital plans. In my case study, geometry and track component data were collected over a 115-mile (185 km) heavy haul Class I railroad subdivision in the US and were analyzed for correlations. One of the primary challenges to using track-related data collected from multiple inspection systems on different days is aligning datasets. In this research, datasets are aligned using fixed assets (switches and crossings). After aligning the datasets, fixed windows and aggregation functions are used to analyze the data. Correlation matrices and scatter plots of static data from both technologies showed little correlation between the two datasets. This suggests that railroads should consider the use of both technologies to comply with federal regulations, monitor the condition of their components and infrastructure, and ensure the safe movement of trains. Additionally, a trending framework is developed that is suitable for both geometry and component data, providing useful information to develop comprehensive maintenance plans to facilitate reliable and efficient passenger and freight movement."]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Development of relationships and trending methodologies for railroad track component and geometry data"]}]}],"canonical_facts":{"dc:contributor":["Edwards, John Riley"],"dc:creator":["Morgado Bilheri T Carvalho, Arthur"],"dc:date":["2023-12","2023-12-07"],"dc:description":["Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2024-03-01 without embargo terms","The student, Arthur Morgado Bilheri T Carvalho, accepted the attached license on 2023-12-06 at 09:31.","The student, Arthur Morgado Bilheri T Carvalho, submitted this Thesis for approval on 2023-12-06 at 09:32.","This Thesis was approved for publication on 2023-12-07 at 16:27.","DSpace SAF Submission Ingestion Package generated from Vireo submission #20141 on 2024-03-01 at 13:15:27","The safe and efficient movement of trains requires periodic inspection of the geometry of the track system and health of its components. Railroads have used laser-based track geometry testing to comply with regulatory requirements and internal business practices for over 30 years. More recently, these systems have been supplemented by new technologies capable of inspecting many other attributes of the track including subgrade condition, track component health, and ballast profile. Computational advances including machine vision and artificial intelligence, and the application of big data, have drastically increased the value that can be derived from the ever-growing track health dataset. In this thesis, I present a method to manage the flow of data in a railroad, starting from field data collection to multi-year capital plans. In my case study, geometry and track component data were collected over a 115-mile (185 km) heavy haul Class I railroad subdivision in the US and were analyzed for correlations. One of the primary challenges to using track-related data collected from multiple inspection systems on different days is aligning datasets. In this research, datasets are aligned using fixed assets (switches and crossings). After aligning the datasets, fixed windows and aggregation functions are used to analyze the data. Correlation matrices and scatter plots of static data from both technologies showed little correlation between the two datasets. This suggests that railroads should consider the use of both technologies to comply with federal regulations, monitor the condition of their components and infrastructure, and ensure the safe movement of trains. Additionally, a trending framework is developed that is suitable for both geometry and component data, providing useful information to develop comprehensive maintenance plans to facilitate reliable and efficient passenger and freight movement."],"dc:format":["application/pdf"],"dc:identifier":["https://hdl.handle.net/2142/122064"],"dc:language":["en","eng"],"dc:rights":["Copyright 2023 Arthur Morgado Bilheri T Carvalho"],"dc:subject":["Railway","Track","Geometry","Degradation"],"dc:title":["Development of relationships and trending methodologies for railroad track component and geometry data"],"dc:type":["text"],"thesis:degree_discipline":["Civil Engineering"],"thesis:degree_level":["Thesis"],"thesis:degree_name":["M.S."],"thesis:institution_name":["University of Illinois at Urbana-Champaign"]},"updated_at":"2026-07-22T22:25:00Z"}