FIELD: pipes.
SUBSTANCE: invention can be applied to evaluation of geometrical sizes of wall defects in pipe section and weld seams by data of magnetic in-pipe flaw detector. Invention consists in that evaluation of geometrical sizes of wall defects in pipe section and weld seams by data of magnetic in-pipe flaw detector is performed by means of universal neural network model, which implements method consisting in propagation of error signals from neural network outputs to its inputs, in direction opposite to straight signal propagation in normal operating mode. Neural network is trained using standard algorithm of reverse error propagation.
EFFECT: technical result is possibility to assess length, width, and depth of "metal loss" type defect according to magnetic in-pipe flaw detector, using universal neural network model, suitable for flaw detectors with different diameters and magnetic systems.
1 cl, 1 dwg
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Authors
Dates
2016-07-20—Published
2015-05-19—Filed