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

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.

Keywords

• gas pipeline steel
• fracture process
• acoustic emission
• <i>k-means</i> algorithm
• time-frequency analysis
• wavelet analysis