Paper title
“Automatic Detection of High Temperature Hydrogen Attack Defects from Ultrasonic
A-scan Signals”
Authors:
Ahmed Yamani and Mohamed Deriche
Affiliation:
King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia
Abstract
— Successful application of the rich collection of classification algorithms to
nondestructive testing signals depends heavily on the availability of adequate
and representative sets of training examples, whose acquisition can often be
very expensive and time consuming. In this paper, an out-of-service pressure
vessel known to have lots of high temperature hydrogen attach (HTHA) defects is
used to develop in a cost effective manner a database of ultrasonic A-scan
signals. To test how adequate and representative these sets of A-scan signals
are, a basic feature extraction method, coupled with a primitive classifier is
shown to distinguish accurately the hydrogen attack from geometrically similar
defects. |
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