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Architecture optimization of acoustic emission source recognition neural networks
Chlada, Milan ; Blaháček, Michal ; Převorovský, Zdeněk
In the contribution, the acoustic emission model source recognition method is described and discussed. Weighted combinations of tree model pulses were excited in aircraft structure. For the original weight estimation, various artificial neural networks were tested. Within the architecture optimization, the sensitivity analysis of trained networks enabled targeted inputs reduction towards the minimal number of parameters needed for reliable model sources apportionment estimation.

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