"Detection of Internal Defects of Material on the Basis of Performance Spectral Density Analysis"@en . . "LT - Litevsk\u00E1 republika" . . "27360" . "1392-8716" . "12" . "1"^^ . . . "Detection of Internal Defects of Material on the Basis of Performance Spectral Density Analysis" . . "Detection of Internal Defects of Material on the Basis of Performance Spectral Density Analysis" . . . . "000286017700021" . . . . "2"^^ . "RIV/61989100:27360/10:86075877!RIV11-GA0-27360___" . . "JOURNAL OF VIBROENGINEERING" . "RIV/61989100:27360/10:86075877" . "P(1M0567), P(GA102/08/1429), S" . "4" . "Frischer, Robert" . "Analysis; Density; Spectral; Performance; Basis; Material; Defects; Internal; Detection"@en . . . . "Krejcar, Ond\u0159ej" . "Detection of Internal Defects of Material on the Basis of Performance Spectral Density Analysis"@en . "11"^^ . . . . . . "The developed approach for nondestructive diagnosis of solid objects is described in this article. This is accomplished by means of software analysis of oscillatory spectra (possibly acoustic emissions,) which is formed while running the monitored device or in unexpected situations. The principle of this method is based on the analysis of spectrum from received signal, its subsequent processing in MatLab and following sample comparison in Statistica program. The last step (comparison of samples) is the most important because it enables determination with some certainty the actual condition of the examined object. The processed samples are currently compared only visually. On the other hand, in applying this approach they are subject to the analysis with the assistance of neural network (Statistica program)." . "253644" . . . . "[6F9F066AFB9D]" . "The developed approach for nondestructive diagnosis of solid objects is described in this article. This is accomplished by means of software analysis of oscillatory spectra (possibly acoustic emissions,) which is formed while running the monitored device or in unexpected situations. The principle of this method is based on the analysis of spectrum from received signal, its subsequent processing in MatLab and following sample comparison in Statistica program. The last step (comparison of samples) is the most important because it enables determination with some certainty the actual condition of the examined object. The processed samples are currently compared only visually. On the other hand, in applying this approach they are subject to the analysis with the assistance of neural network (Statistica program)."@en .