Machine
intelligence
and Pattern
Analysis
Laboratory
Project
II:
Discrimination of echoes in computer based ultrasonic flaw detection
for CAD modeled steel pieces
Aims:
(1) To develop techniques from artificial
intelligence, machine learning and data mining that can filter and
discriminate mode-converted echoes in UT flaw detection, and to
(2) incorporate domain knowledge from the CAD model of the piece
that describes its design features.
Colaborators:
Guy Cotteril and John Perceval (CSPope industrial partner)
Funding:
ARC SPIRT grant
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