Title:
Methods And Systems For Classifying The Type And Severity Of Defects In Welds

dc.contributor.patentcreator Ume, Ifeanyi Charles
dc.contributor.patentcreator Li, Renfu
dc.contributor.patentcreator Rogge, Matthew
dc.contributor.patentcreator Wu, Tsun-yen
dc.date.accessioned 2017-05-12T14:29:13Z
dc.date.available 2017-05-12T14:29:13Z
dc.date.filed 8/3/2009
dc.date.issued 4/3/2012
dc.description.abstract A method for determining the type of a defect in a weld may include determining a defect location and a corresponding defect signal by analyzing ultrasonic response signals collected from a plurality of measurement locations along the weld. The defect signal and the plurality of defect proximity signals corresponding to ultrasonic response signals from measurement locations on each side of the defect location may then be input into a trained artificial neural network. The trained artificial neural network may be operable to identify the type of the defect located at the defect location based on the defect signal and the plurality of defect proximity signals and output the type of the defect located at the defect location. The trained artificial neural network may also be operable to determine a defect severity classification based on the defect signal and the plurality of defect proximity signals and output the severity classification.
dc.description.assignee Georgia Tech Research Corporation
dc.identifier.cpc G01N29/11
dc.identifier.cpc G01N29/4445
dc.identifier.cpc G01N29/4481
dc.identifier.patentapplicationnumber 12/534581
dc.identifier.patentnumber 8146429
dc.identifier.uri http://hdl.handle.net/1853/58036
dc.identifier.uspc 73/622
dc.title Methods And Systems For Classifying The Type And Severity Of Defects In Welds
dc.type Text
dc.type.genre Patent
dspace.entity.type Publication
local.contributor.corporatename Georgia Institute of Technology
local.relation.ispartofseries Georgia Tech Patents
relation.isOrgUnitOfPublication cc30e153-7a64-4ae2-9b1d-5436686785e3
relation.isSeriesOfPublication 0f49c79d-4efb-4bd9-b060-5c7f9191b9da
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