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Detection and characterization of stainless steel SCC by the analysis of crack related acoustic emission
ID Kovač, Jaka (Author), ID Legat, Andraž (Author), ID Zajec, Bojan (Author), ID Kosec, Tadeja (Author), ID Govekar, Edvard (Author)

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Language:English
Keywords:physics, acoustic emission, signal processing, stress-corrosion cracking, spectral analysis
Work type:Article
Typology:1.01 - Original Scientific Article
Organization:FS - Faculty of Mechanical Engineering
Publication status:Published
Publication version:Author Accepted Manuscript
Year:2015
Number of pages:Str. 312-322
Numbering:Vol. 62
PID:20.500.12556/RUL-105930 This link opens in a new window
UDC:534(045)
ISSN on article:0041-624X
DOI:10.1016/j.ultras.2015.06.005 This link opens in a new window
COBISS.SI-ID:14050843 This link opens in a new window
Publication date in RUL:24.12.2018
Views:1363
Downloads:768
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Record is a part of a journal

Title:Ultrasonics
Shortened title:Ultrasonics
Publisher:Butterworth Scientific
ISSN:0041-624X
COBISS.SI-ID:26569728 This link opens in a new window

Secondary language

Language:Slovenian
Abstract:
In the paper the results of the acoustic emission (AE) based detection and characterization of stress-corrosion cracking (SCC) in stainless steel are presented. As supportive methods for AE interpretation, electrochemical noise, specimen elongation measurements, and digital imaging of the specimen surface were used. Based on the defined qualitative and quantitative time and power spectra characteristics of the AE bursts, a manual and an automatic procedure for the detection of crack related AE bursts were introduced. The results of the analysis of the crack related AE bursts indicate that the AE method is capable of detecting large scale cracks, where, apart from intergranular crack propagation, also some small ductile fractures occur. The sizes of the corresponding ductile fracture areas can be estimated based on a relative comparison of the energies of the detected AE bursts. It has also been shown that AE burst time and power spectra features can be successfully used for the automatic detection of SCC.

Keywords:fizika, ultrazvok, akustična emisija, korozijsko pokanje, spektralna analiza, pokanje, procesiranje signalov

Projects

Funder:ARRS - Slovenian Research Agency
Project number:P2-0241, P2-0273
Name:Sinergetika kompleksnih sistemov in procesov, Gradbeni objekti in materiali

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