National Repository of Grey Literature 51 records found  beginprevious42 - 51  jump to record: Search took 0.01 seconds. 
Lokalizace zdrojů AE pomocí neuronových sítí na základě signálových parametrů
Chlada, Milan ; Blaháček, Michal ; Převorovský, Zdeněk
The new method of the AE source location by artificial neural networks, which process extracted signal parameters and do not consider the arrival time differences, is introduced.
AE Source Localization and Emission Parameters Correction Using Neural Networks
Chlada, Milan ; Blaháček, Michal ; Převorovský, Zdeněk
In the contribution, the new method, based on artificial neural networks (ANN), is proposed, which estimates the AE source location by processing other extracted signal parameters instead of arrival time differences.The complete signal inversion is not necessary for good diagnostic decision, and a simplified correction of the most important signal parameters by trained neural networks is sufficient.
Threshold counting in wavelet domain
Chlada, Milan ; Převorovský, Zdeněk
New AE signal parameters (wavelet counts) are introduced using atwo-level threshold counting of wavelet coefficients. The application of wavelet counts is illustrated in three examples of both real and simulated AE data. The significance of various classicaland newly introduced AE signal parameters used to AE source identification is tested using theneural network sensitivity and factor analyses.
Selection of signal parameters for analysis of AE sources
Chlada, Milan ; Převorovský, Zdeněk ; Mrázová, I.
The paper describes several methods of signal feature set selection, applied on boath experimental and simulated AE data.
Acoustic emission and feature subset selection based on sensitivity analysis
Chlada, Milan ; Mrázová, I. ; Převorovský, Zdeněk
Technical report describes several methods of feature subset selection based on sensitivity analysis of neural networks.
Acousic emission and feature subset selection based on sensitivity analysis
Chlada, Milan ; Mrázová, I. ; Převorovský, Zdeněk
The paper describes several methods of feature subset selection, applied on both experimental and simulated data.
Akusto-ultrazvukové hodnocení a optický záznam strukturních změn během mechanického zatěžování materiálů s tvarovou pamětí na bázi CuAlNi / Z 1264/00/
Landa, Michal ; Novák, V. ; Chlada, Milan ; Urbánek, Přemysl ; Zídek, Jan
Zpráva obsahuje popis a kvalitativní interpretaci výsledků měření změn akustických vlastností během martenzitické transformace SMA materiálů.
Korekce parametrů signálu AE pomocí neuronových sítí
Chlada, Milan ; Převorovský, Zdeněk ; Vodička, Josef
In the contribution, the new approach for conversion of signal parameters, evaluated at various transducers, to one reference location in source vicinity is described. This reduced inverse problem is solved using artificial neural networks.

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