FIELD: test equipment.
SUBSTANCE: invention relates to test equipment and is used to determine temperature of viscous-brittle transition and detection of acoustic emission signal based on classification of pulses using an artificial neural network. Sample mounted on table of hardness meter is subjected to indentation at different temperatures with registration of acoustic emission signal, obtained acoustic emission signal is subjected to treatment with separation of separate pulses, determination of their parameters and their subsequent classification using trained artificial neural network, and the temperature of the viscous-brittle transition is taken to be the temperature at which the number of pulses characterizing brittle and viscous mechanisms of destruction coincide.
EFFECT: high accuracy of estimating temperature of a viscous-brittle metal transition.
1 cl, 4 dwg, 1 tbl
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Authors
Dates
2020-04-23—Published
2019-12-09—Filed