Identification of the Fracture Process in Gas Pipeline Steel Based on the Analysis of AE Signals

The paper presents the results of tests conducted to identify the damage process in specimens collected from the steel of a gas pipeline. The tests concerned specimens made of S235 steel subject to quasi-static loading—uniaxial tension until failure. Acoustic emission (AE) signals were recorded duri...

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Published inMaterials Vol. 15; no. 7; p. 2659
Main Authors Świt, Grzegorz, Dzioba, Ihor, Adamczak-Bugno, Anna, Krampikowska, Aleksandra
Format Journal Article
LanguageEnglish
Published Switzerland MDPI AG 04.04.2022
MDPI
Subjects
Acoustic emission
Acoustics
Cluster analysis
Clustering
Damage detection
Elongation
Frequency spectrum
Gas pipelines
Laboratories
Natural gas
Sensors
Signal processing
Structural steels
Tensile strength
Time-frequency analysis
Vector quantization
gas pipeline steel
acoustic emission
fracture process
time-frequency analysis
wavelet analysis
k-means algorithm
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Abstract The paper presents the results of tests conducted to identify the damage process in specimens collected from the steel of a gas pipeline. The tests concerned specimens made of S235 steel subject to quasi-static loading—uniaxial tension until failure. Acoustic emission (AE) signals were recorded during the loading process along with force and elongation signals. Sections were collected from previously loaded specimens and subjected to microstructural examinations to determine the nature of material damage at different strain stages. The recorded AE signals were analyzed using the k-means clustering method, as well as time-frequency analysis. The results of metallographic tests and analysis of AE signals identified frequency spectra characteristic of different stages of the process of material damage.
AbstractList The paper presents the results of tests conducted to identify the damage process in specimens collected from the steel of a gas pipeline. The tests concerned specimens made of S235 steel subject to quasi-static loading—uniaxial tension until failure. Acoustic emission (AE) signals were recorded during the loading process along with force and elongation signals. Sections were collected from previously loaded specimens and subjected to microstructural examinations to determine the nature of material damage at different strain stages. The recorded AE signals were analyzed using the k-means clustering method, as well as time-frequency analysis. The results of metallographic tests and analysis of AE signals identified frequency spectra characteristic of different stages of the process of material damage.
The paper presents the results of tests conducted to identify the damage process in specimens collected from the steel of a gas pipeline. The tests concerned specimens made of S235 steel subject to quasi-static loading-uniaxial tension until failure. Acoustic emission (AE) signals were recorded during the loading process along with force and elongation signals. Sections were collected from previously loaded specimens and subjected to microstructural examinations to determine the nature of material damage at different strain stages. The recorded AE signals were analyzed using the k-means clustering method, as well as time-frequency analysis. The results of metallographic tests and analysis of AE signals identified frequency spectra characteristic of different stages of the process of material damage.The paper presents the results of tests conducted to identify the damage process in specimens collected from the steel of a gas pipeline. The tests concerned specimens made of S235 steel subject to quasi-static loading-uniaxial tension until failure. Acoustic emission (AE) signals were recorded during the loading process along with force and elongation signals. Sections were collected from previously loaded specimens and subjected to microstructural examinations to determine the nature of material damage at different strain stages. The recorded AE signals were analyzed using the k-means clustering method, as well as time-frequency analysis. The results of metallographic tests and analysis of AE signals identified frequency spectra characteristic of different stages of the process of material damage.
The paper presents the results of tests conducted to identify the damage process in specimens collected from the steel of a gas pipeline. The tests concerned specimens made of S235 steel subject to quasi-static loading—uniaxial tension until failure. Acoustic emission (AE) signals were recorded during the loading process along with force and elongation signals. Sections were collected from previously loaded specimens and subjected to microstructural examinations to determine the nature of material damage at different strain stages. The recorded AE signals were analyzed using the k-means clustering method, as well as time-frequency analysis. The results of metallographic tests and analysis of AE signals identified frequency spectra characteristic of different stages of the process of material damage.
The paper presents the results of tests conducted to identify the damage process in specimens collected from the steel of a gas pipeline. The tests concerned specimens made of S235 steel subject to quasi-static loading-uniaxial tension until failure. Acoustic emission (AE) signals were recorded during the loading process along with force and elongation signals. Sections were collected from previously loaded specimens and subjected to microstructural examinations to determine the nature of material damage at different strain stages. The recorded AE signals were analyzed using the clustering method, as well as time-frequency analysis. The results of metallographic tests and analysis of AE signals identified frequency spectra characteristic of different stages of the process of material damage.
Author Adamczak-Bugno, Anna
Dzioba, Ihor
Świt, Grzegorz
Krampikowska, Aleksandra
AuthorAffiliation 1 Faculty of Civil Engineering and Architecture, Kielce University of Technology, 25-314 Kielce, Poland; gswit@tu.kielce.pl (G.Ś.); akramp@tu.kielce.pl (A.K.)
2 Faculty of Mechatronics and Mechanical Engineering, Kielce University of Technology, 25-314 Kielce, Poland; pkmid@tu.kielce.pl
AuthorAffiliation_xml – name: 1 Faculty of Civil Engineering and Architecture, Kielce University of Technology, 25-314 Kielce, Poland; gswit@tu.kielce.pl (G.Ś.); akramp@tu.kielce.pl (A.K.)
– name: 2 Faculty of Mechatronics and Mechanical Engineering, Kielce University of Technology, 25-314 Kielce, Poland; pkmid@tu.kielce.pl
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Keywords gas pipeline steel
acoustic emission
fracture process
time-frequency analysis
wavelet analysis
k-means algorithm
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Snippet The paper presents the results of tests conducted to identify the damage process in specimens collected from the steel of a gas pipeline. The tests concerned...
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StartPage 2659
SubjectTerms Acoustic emission
Acoustics
Cluster analysis
Clustering
Damage detection
Elongation
Frequency spectrum
Gas pipelines
Laboratories
Natural gas
Sensors
Signal processing
Structural steels
Tensile strength
Time-frequency analysis
Vector quantization
Title Identification of the Fracture Process in Gas Pipeline Steel Based on the Analysis of AE Signals
URI https://www.ncbi.nlm.nih.gov/pubmed/35407991
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