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Ground Penetrating Radar Method In Steel Bars Detecting Of Reinforce Concrete Structures

Posted on:2005-01-29Degree:MasterType:Thesis
Country:ChinaCandidate:M H XuFull Text:PDF
GTID:2132360125962612Subject:Structural engineering
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Among the Non-Destructive Test methods that are used in the inspection of concrete structures, Ground Penetrating Radar(GPR) has some particular superiorities. So it is more and more attractive to the engineering fields. But up till now, there are few studies in GPR investigations of reinforce concrete structures, it affects the popularization of this technique. In order to resolve the difficulties in applying GPR to reinforce concrete structures, a series of studies have been made in this paper. These difficulties includes:l)the selection of concrete relative permittivity, this value will affect the surveying precision of concrete depths(or thickness) directly;2)the interaction of radar waves that are reflected from rebar groups;3)GPR inspection of rebar diameters, it is an difficulty that is not resolved by GPR survey.We adopt a model-test method to deal with the former two problems. First, Through the test studies of the interaction of radar waves that are reflected from rebar groups, we get some instructional experiences. Second, By surveying two concrete specimens, we find the relationship between concrete depths H and the relative permittivities of concrete E ,: ε r will increase along with the increment of depths. So we brought forward a practical method that ε r should be assessed according to subsections of H.A example shows that this method can improve the precision of the inspection of concrete depths. Finally, we probed into the auto identification of rebar size using a BP neural network. We take each half positive radar wave that collected from laboratory-cast concrete specimens as the identifying object. Then we select wave crest, energy of wave , wavelength and wave slope as the inputs of the BP network. We also subdivide the BP network into several networks which improved the precision of network. The outputs of the networks showed that we succeeded in assessing rebar sizes by the BP networks and the results meet the demand of engineer precision.Our work is original in the application of GPR to the nondestructive test of reinforce concrete structures and we solved some difficulties that are interesting and hard to settle. So our work has bright future in engineer application.
Keywords/Search Tags:Ground Penetrating Radar (GPR), reinforced concrete structures, Non-Destructive Testing(NDT), relative permittivity, diameter of rebar, Back-Propagation neural networks
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