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

• Published in: Materials Vol. 15; no. 7; p. 2659
• Main Authors: Świt, Grzegorz, Dzioba, Ihor, Adamczak-Bugno, Anna, Krampikowska, Aleksandra
• Format: Journal Article
• Language: English
• 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

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...