EPSRC Reference: |
GR/L27619/01 |
Title: |
INTERPRETATION OF SUB-SURFACE RADAR IMAGES OF REINFORCED CONCRETE USING ARTIFICIAL NEURAL NETWORKS |
Principal Investigator: |
Molyneaux, Dr T |
Other Investigators: |
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Researcher Co-Investigators: |
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Project Partners: |
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Department: |
Civil Engineering |
Organisation: |
University of Liverpool |
Scheme: |
Standard Research (Pre-FEC) |
Starts: |
26 May 1997 |
Ends: |
25 May 1999 |
Value (£): |
149,157
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EPSRC Research Topic Classifications: |
Instrumentation Eng. & Dev. |
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EPSRC Industrial Sector Classifications: |
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Related Grants: |
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Panel History: |
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Summary on Grant Application Form |
Sub-surface radar is widely used to evaluate the geometry and integrity of continuous features in concrete structures, eg. delamination of bridge decks. The study of singularities such as reinforcing bars or localised voids is more problematic. The proposed study will address the possibilty of improving the radar image interpretation by the use of artificial neural networks (ANNs). Radar signal data collected from a number of real concrete specimens will be used to build a database of reinforcing bar and void images for a range of geometries and configurations. This database will them be used to investigate the evaluation of singularity size, depth and form using a number of ANN approaches. Sucessful techniques will be incorporated into a hierarchical system incorporating conventional radar knowledge and simple processing capability together with an array of ANNs designed to assist in the post-processing of radar results.
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Key Findings |
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Potential use in non-academic contexts |
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Impacts |
Description |
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Summary |
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Date Materialised |
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Sectors submitted by the Researcher |
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Project URL: |
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Further Information: |
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Organisation Website: |
http://www.liv.ac.uk |