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Project

#10 Infrastructure Monitoring for Gradual Damage Detection Form an Inservice Light Rail Vehicle


Principal Investigator
Jacobo Bielak
Status
Completed
Start Date
Jan. 1, 2017
End Date
Aug. 31, 2018
Project Type
Research Applied
Grant Program
MAP-21 TSET National (2013 - 2018)
Grant Cycle
2017 TSET UTC
Visibility
Public

Abstract

Globally, infrastructure is a vital asset for economic prosperity. However, condition assessments to ensure the continued safe operation of these assets tend to be subjective and infrequent. We are developing a low-cost, objective method to continuously monitor rail systems from the vibrations recorded in a passing train as a complement to traditional inspection techniques. With previous support from the University Transportation Center, we have established a long-term monitoring project with the Port Authority of Allegheny County. We have developed and deployed a robust automatic data acquisition and management system. Through this deployment we have been testing and refining our technique. We have instrumented two of Pittsburgh’s light
rail vehicles and have been monitoring the rail system from the vibrations in the operational vehicle over the last three years. Our long-term objective is to provide accurate, rapid, nearly continuous assessments of the tracks, track structures and bridges along the line as cost-efficiently as possible. We already have obtained useful results, as we have been able to detect discrete changes in the recorded signals after construction activity on both the track and ballast. We have also developed a systematic method of data analysis to fuse data from multiple instrumented vehicles, and better detect changes in the condition of the rail/track system, and, thus, provide better insights for the Port Authority on high-priority maintenance issues. Our next immediate challenge is to develop suitable algorithms that will enable our monitoring system to detect small gradual continuous degradation in the rail/track system. This is a key step for making the monitoring system a practical damage detection tool. In addition, even though  we have recorded vehicle motion as it moves along the entire track, until now, we have analyzed only data recorded on parts of the line that are supported on firm ground. During the course of the proposed project, we plan to begin analyzing also data from the vehicles as they traverse bridges within the line. Ultimately, our goal is to develop an infrastructure asset management technology that can serve not only the Port Authority of Allegheny County but also infrastructure owners for a variety of transportation modes. Through this improved maintenance technology, we will enable safer more efficient transportation.    
Description

    
Timeline

    
Strategic Description / RD&T

    
Deployment Plan

    
Expected Outcomes/Impacts

    
Expected Outputs

    
TRID


    

Individuals Involved

Email Name Affiliation Role Position
marioberges@cmu.edu Berges, Mario CEE Co-PI Faculty - Adjunct
jbielak@cmu.edu Bielak, Jacobo CEE PI Faculty - Tenured
noh@cmu.edu Noh, Hae Young CEE Co-PI Faculty - Adjunct

Budget

Amount of UTC Funds Awarded
$127500.00
Total Project Budget (from all funding sources)
$127500.00

Documents

Type Name Uploaded
Presentation Damage Diagnosis Algorithms for Indirect Structural Health Monitoring of Bridges Sept. 30, 2017, 4:56 p.m.
Presentation Structures as Sensors: Indirect Monitoring of Humans and Surrounding Sept. 30, 2017, 4:56 p.m.
Presentation Structures as Sensors: Indirect Monitoring of Humans and Surrounding Sept. 30, 2017, 4:56 p.m.
Presentation Structures as Sensors: Indirect Monitoring of Humans and Surrounding Sept. 30, 2017, 4:56 p.m.
Progress Report 10_Progress_Report_2016-10-01 Sept. 30, 2017, 4:56 p.m.
Progress Report 10_Progress_Report_2017-09-30 Oct. 5, 2017, 10:02 a.m.
Presentation Smart Infrastructure/Buildings as the Backbone of Smart Cities March 31, 2018, 6:37 p.m.
Progress Report 10_Progress_Report_2018-03-31 March 31, 2018, 6:42 p.m.
Final Report 10_utc_final_report-light_rail.2018.pdf Nov. 12, 2018, 5:14 a.m.
Publication Track-monitoring from the dynamic response of an operational train March 21, 2021, 7:52 p.m.
Publication A data fusion approach for track monitoring from multiple in-service trains March 21, 2021, 7:53 p.m.

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