Title page for ETD etd-081199-184611

Type of Document Dissertation
Author Scott, Michael Leon
Author's Email Address miscott@vt.edu
URN etd-081199-184611
Title Automated Characterization of Bridge Deck Distress Using Pattern Recognition Analysis of Ground Penetrating Radar Data
Degree PhD
Department Civil Engineering
Advisory Committee
Advisor Name Title
Duke, John C. Jr. Committee Co-Chair
Weyers, Richard E. Committee Co-Chair
Brown, Gary S. Committee Member
Conners, Richard W. Committee Member
Flintsch, Gerardo W. Committee Member
  • data processing
  • bridge deck, ground penetrating radar, pattern rec
Date of Defense 1999-08-02
Availability unrestricted
Many problems are involved with intspecting and evaluating the condition of

bridges in the United States. Concrete bridge deck inspection and evaluation

presents one of the largest problems. The deterioration of these concrete

decks progresses more rapidly than any other bridge component, which leads to

early concrete deck replacements that must be done before the bridge

superstructure needs to be replaced. The primary cause of deterioration in

these concrete bridge decks is corrosion-induced concrete cracking, which

frequently results in delaminations. Delamination distress increases the life

cycle cost of maintaining a concrete bridge deck, particularly when it is not

detected early on. Early detection of delamination distress can facilitate

economical repair and rehabilitation work, but bridge engineers must recommend

deck replacement if repairs are delayed too long or inspection tools cannot detect

delaminations early enough.

The Federal Highway Administration has responded to the need for a better

bridge deck inspection tool by contracting Lawrence Livermore National Laboratory

to develop two new prototype ground penetrating radar systems. These two systems

generate three-dimensional data that provide a representation of features that lie

below the bridge deck surface. Both of these systems produce large amounts of

data for an individual bridge deck, which makes automated data processing very

desirable. The primary goal of the automated processing is to characterize bridge

deck distress represented in the data. This study presents data collected from

sample bridge deck sections using one of the prototype systems. It also describes

the development and implementation of appropriate methods for automating data

processing. The automated data processing is accomplished using image processing

and pattern recognition algorithms developed in the study.

  Filename       Size       Approximate Download Time (Hours:Minutes:Seconds) 
 28.8 Modem   56K Modem   ISDN (64 Kb)   ISDN (128 Kb)   Higher-speed Access 
  appendix.pdf 860.26 Kb 00:03:58 00:02:02 00:01:47 00:00:53 00:00:04
  chapter1.pdf 722.26 Kb 00:03:20 00:01:43 00:01:30 00:00:45 00:00:03
  chapter2.pdf 1.66 Mb 00:07:39 00:03:56 00:03:26 00:01:43 00:00:08
  chapter3.pdf 520.46 Kb 00:02:24 00:01:14 00:01:05 00:00:32 00:00:02
  chapter4.pdf 614.83 Kb 00:02:50 00:01:27 00:01:16 00:00:38 00:00:03
  chapter5.pdf 13.79 Kb 00:00:03 00:00:01 00:00:01 < 00:00:01 < 00:00:01
  front.pdf 22.73 Kb 00:00:06 00:00:03 00:00:02 00:00:01 < 00:00:01
  references.pdf 12.90 Kb 00:00:03 00:00:01 00:00:01 < 00:00:01 < 00:00:01
  vita.pdf 5.08 Kb 00:00:01 < 00:00:01 < 00:00:01 < 00:00:01 < 00:00:01

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