Principal Investigator

Jacobo Bielak

Status

Completed

Start Date

Jan. 1, 2014

End Date

Dec. 31, 2014

Project Type

Research Advanced

Grant Program

MAP-21 TSET - Tier 1 (2012 - 2016)

Grant Cycle

2014 TSET UTC

Visibility

Public

Abstract

The purpose of this project is to develop an indirect SHM approach, in which one makes use of vibration data collected from sensors installed on vehicles as they traverse the bridge or other infrastructure, rather than from sensors installed on the structure itself. Our vision is that by continuously collecting data from many vehicles, it will become possible to acquire a timely and comprehensive view of the status of the infrastructure a low cost and plan for its maintenance accordingly. An initial exploratory study based entirely on mathematical models and computational simulations allowed us to demonstrate the feasibility of our indirect monitoring approach for these mathematical models and the desirability of testing this technique on physical models. Subsequently we conducted an experimental study using, first a laboratory model, and then a field experiment in the East Campus Garage. These tests are relatively simple experiments; they have been used to examine and calibrate our classification methodology and have been an attempt to create the type of scenario we might encounter later on. In order to examine actual damage conditions under a controlled setting, in 2014 we plan to conduct additional experiments with the lab model, in which we will gradually create increasingly large cracks in the beams and girders; (ii) We will complete the analysis of the data recorded during the East Campus Garage experiments; (iii) Our main focus during this period will be on the Light Rail Line. Since sudden damage to bridges occurs only sporadically, we will study damage in reverse; that is, in coordination with the Port Authority we will select bridges that are scheduled to be retrofitted and will examine whether we can verify with our methodology that changes occur to a bridge during the retrofit or repair from its initial damaged state; (iv) We plan to concentrate also on damage detection in the railway track on “the T.” Such damage is a much more common occurrence than bridge damage and of great interest to the railway industry. We expect that such damage will also affect the dynamic behavior of the train and that it might be possible to detect such changes from the accelerometer signals using the same general detection methodology we are developing for damage bridge detection.    

Description

-

Timeline

-

Strategic Description / RD&T

Deployment Plan

-

Expected Outcomes/Impacts

-

Expected Outputs

TRID

Individuals Involved

Email	Name	Affiliation	Role	Position
jbielak@cmu.edu	Bielak, Jacobo	CEE	PI	Faculty - Tenured

Budget

Amount of UTC Funds Awarded

$90000.00

Total Project Budget (from all funding sources)

$90000.00

Documents

Type	Name	Uploaded
Final Report	144_-_UTC_Final_report_bridge_project_2014.pdf	July 20, 2018, 9:10 a.m.
Publication	Knowledge transfer between bridges for drive-by monitoring using adversarial and multi-task learning	March 21, 2021, 7:47 p.m.
Publication	An expectation-maximization algorithm-based framework for vehicle-vibration-based indirect structural health monitoring of bridges	March 21, 2021, 7:48 p.m.
Publication	Diagnosis algorithms for indirect structural health monitoring of a bridge model via dimensionality reduction	March 21, 2021, 7:48 p.m.
Publication	A damage localization and quantification algorithm for indirect structural health monitoring of bridges using multi-task learning	March 21, 2021, 7:49 p.m.
Publication	Damage-sensitive and domain-invariant feature extraction for vehicle-vibration-based bridge health monitoring	March 21, 2021, 7:50 p.m.

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