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Predicting the mechanical condition of materials from the spectral characteristics of an acoustic-emission signal

✍ Scribed by V. G. Grishko; S. I. Likhatskii; V. A. Strel'chenko; Yu. I. Lykov; A. I. Gorbunov; Yu. V. Dobrovol'skii


Book ID
112556019
Publisher
Springer
Year
1984
Tongue
English
Weight
314 KB
Volume
16
Category
Article
ISSN
0039-2316

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An artificial neural (ANN) network was trained to recognize the stress intensity factor in the interval from microcrack to fracture from acoustic emission (AE) measurements on compact tension specimens. The specimens were made from structural steel SWS490B whilst the ANN had a 5-14-1 structure. The