Intelligent Structural Health Monitoring of Vehicular Bridges Using Fiber Optic Sensors to Detect Acoustic Emission

Yan Zhu; Zhu, Yinian; Regez, Brad; Balogun, Oluwaseyi; Krishnaswamy, Sridhar

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Intelligent Structural Health Monitoring of Vehicular Bridges Using Fiber Optic Sensors to Detect Acoustic Emission

2011-01-28
By Yan Zhu ; Zhu, Yinian ; Regez, Brad

File Language:

English

Details

Creators:

Yan Zhu ; Zhu, Yinian ; Regez, Brad ; Balogun, Oluwaseyi ; Krishnaswamy, Sridhar
Corporate Creators:

Northwestern University (Evanston, Ill.)
Corporate Contributors:

United States. Dept. of Transportation. Research and Innovative Technology Administration
Subject/TRT Terms:
Resource Type:

Tech Report
Geographical Coverage:

Illinois ; United States
OCLC Number:

746952931
Corporate Publisher:

Northwestern University (Evanston, Ill.). Center for the Commercialization of Innovative Transportation Technology
NTL Classification:

NTL-HIGHWAY/ROAD TRANSPORTATION-Bridges and Structures
Abstract:

The recent collapse of the I-35W Mississippi River Bridge in Minneapolis has spawned a growing interest in the development of reliable techniques for evaluating the structural integrity of civil infrastructure. Current inspection techniques tailored to vehicular bridges in particular are widely based on short-term or intermittent monitoring schedules. While these techniques have had reasonable success in assessing the structural integrity of bridges, there are unanswered questions about their effectiveness for monitoring sudden adverse structural changes that can lead to catastrophic bridge failure. Structural health monitoring (SHM) is an alternative inspection paradigm that provides the potential for long-term monitoring of integrity of large-scale structures.
Format:

PDF
Download URL:

https://rosap.ntl.bts.gov/view/dot/22908/dot_22908_DS1.pdf
File Type:

[PDF - 1.49 MB]
Collection(s):

University Transportation Centers ; US Transportation Collection
Main Document Checksum:

urn:sha-512:5198401be420d42e2b2897718d2f15c8058ed4948cd5ec2776630d205e4d79e95690ced3ad0b477bd2262581ba0eff250b99001ec1a5015f2f6d3c78bd80168c

File Language:

English

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