Identification of out-of-round wheels on heavy-haul railway lines by using ballast pressure data

Qingjie Liu, Xiaoyan Lei, Jerry G. Rose, Qingsong Feng, Teng Wang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

A Model-Based Estimate Method (MBEM) was introduced to estimate wheel-rail force by using track dynamic response data, the estimated result then be used for of OOR wheels identification. The function of dynamic force transfer between the wheel-rail force and tie displacement was developed based on a double layers track model. A case study was conducted to verify the result. Test equipment was made for tie-ballast interface pressure measurement. The equipment was installed on a heavy-haul railway line in the United States, long-term monitoring on ballast pressure was conducted. A series of preprocessing methods were used to obtain the normalized pressure data. According to the comparison between Wheel Impact Load Detector (WILD) data and ballast pressure data, the relationship between ballast pressure and wheel load was established. The wheel-rail force of each wheel was calculated by using the MBEM method.

Original languageEnglish
Title of host publicationStructural Health Monitoring 2019
Subtitle of host publicationEnabling Intelligent Life-Cycle Health Management for Industry Internet of Things (IIOT) - Proceedings of the 12th International Workshop on Structural Health Monitoring
EditorsFu-Kuo Chang, Alfredo Guemes, Fotis Kopsaftopoulos
Pages585-594
Number of pages10
ISBN (Electronic)9781605956015
DOIs
StatePublished - 2019
Event12th International Workshop on Structural Health Monitoring: Enabling Intelligent Life-Cycle Health Management for Industry Internet of Things (IIOT), IWSHM 2019 - Stanford, United States
Duration: Sep 10 2019Sep 12 2019

Publication series

NameStructural Health Monitoring 2019: Enabling Intelligent Life-Cycle Health Management for Industry Internet of Things (IIOT) - Proceedings of the 12th International Workshop on Structural Health Monitoring
Volume1

Conference

Conference12th International Workshop on Structural Health Monitoring: Enabling Intelligent Life-Cycle Health Management for Industry Internet of Things (IIOT), IWSHM 2019
Country/TerritoryUnited States
CityStanford
Period9/10/199/12/19

Bibliographical note

Funding Information:
This research was supported by the Chinese National Natural Science Foundation (51868024) and the National University Rail Center (NURail), a U.S. DOT OST Tier 1 University Transportation Center. Special appreciation is extended to Norfolk Southern Railway for providing the track test site and arranging the logistics and assistance associated with the in-track tests. Also, LB Foster (Salient Systems) Company assisted with the WILD data exportation and data processing techniques.

Publisher Copyright:
© International Workshop on Structural Health Monitoring. All rights reserved.

ASJC Scopus subject areas

  • Computer Science Applications
  • Health Information Management

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