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Monitoring for Underdetermined Underground Structures during Excavation Using Limited Sensor Data

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Date Issued:
2013
Abstract/Description:
A realistic field monitoring application to evaluate close proximity tunneling effects of a new tunnel on an existing tunnel is presented. A blind source separation (BSS)-based monitoring framework was developed using sensor data collected from the existing tunnel while the new tunnel was excavated. The developed monitoring framework is particularly useful to analyze underdetermined systems due to insufficient sensor data for explicit input force-output deformation relations. The analysis results show that the eigen-parameters obtained from the correlation matrix of raw sensor data can be used as excellent indicators to assess the tunnel structural behaviors during the excavation with powerful visualization capability of tunnel lining deformation. Since the presented methodology is data-driven and not limited to a specific sensor type, it can be employed in various proximity excavation monitoring applications.
Title: Monitoring for Underdetermined Underground Structures during Excavation Using Limited Sensor Data.
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Name(s): Mehdawi, Nader, Author
Yun, Hae-Bum, Committee Chair
Sallam, Amr, Committee Member
Chopra, Manoj, Committee Member
, Committee Member
University of Central Florida, Degree Grantor
Type of Resource: text
Date Issued: 2013
Publisher: University of Central Florida
Language(s): English
Abstract/Description: A realistic field monitoring application to evaluate close proximity tunneling effects of a new tunnel on an existing tunnel is presented. A blind source separation (BSS)-based monitoring framework was developed using sensor data collected from the existing tunnel while the new tunnel was excavated. The developed monitoring framework is particularly useful to analyze underdetermined systems due to insufficient sensor data for explicit input force-output deformation relations. The analysis results show that the eigen-parameters obtained from the correlation matrix of raw sensor data can be used as excellent indicators to assess the tunnel structural behaviors during the excavation with powerful visualization capability of tunnel lining deformation. Since the presented methodology is data-driven and not limited to a specific sensor type, it can be employed in various proximity excavation monitoring applications.
Identifier: CFE0004718 (IID), ucf:49834 (fedora)
Note(s): 2013-05-01
M.S.
Engineering and Computer Science, Civil, Environmental and Construction Engineering
Masters
This record was generated from author submitted information.
Subject(s): Monitoring -- Underground Structures -- Sensor Data -- underdetermined
Persistent Link to This Record: http://purl.flvc.org/ucf/fd/CFE0004718
Restrictions on Access: public 2013-05-15
Host Institution: UCF

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