Application of the cluster analysis and time statistic of acoustic emission events from tensile test of a cylindrical rock salt specimen

2019 ◽  
Vol 210 ◽  
pp. 84-94 ◽  
Author(s):  
Gerd Manthei
2019 ◽  
Vol 2019 ◽  
pp. 1-12 ◽  
Author(s):  
Chunping Wang ◽  
Jianfeng Liu ◽  
Lu Wang

Understanding the damage evolution characteristics of rock material is essential to the long-term stability and safety analysis of the underground facility. In this study, a series of cyclic loading tests under tensile or compressive stresses are conducted to investigate the damage evolution, deformation, peak strength, and failure pattern of rock salt. A special attention is paid on the microcracking process by using a 3D acoustic emission (AE) test system. The laboratory tests show that the damage degree of rock salt under compression is the highest, followed by the damage in the direct tensile test. The lowest value of damage is determined by using the Brazilian test. The damage degrees where the damage rate starts to decrease are about 0.83 in the direct tensile test, about 0.75 in the Brazilian test, and about 0.91 in the compression test. The failure mode of rock salt changes from the tensile mode in the uniaxial compression test to the compression-shear mode in the confined compression test at low confinement. But from the confining pressure of 15 MPa, the rock salt displays great plastic dilatant distortion and without appreciable macroscopic fractures. Accordingly, with increasing confining pressure, the positions where the rapid increase in cumulative AE counts occurs and where the AE event with high energy appears are changed, from the beginning of the test at low confinement to the postpeak stage of the test at high confinement.


Author(s):  
Jianfeng Liu ◽  
Yilin Liao ◽  
Chaofu Deng ◽  
Qiangxing Zhang ◽  
Zhicheng Li ◽  
...  

Author(s):  
Zhongzheng Zhang ◽  
Cheng Ye ◽  
Jun Jiang

In order to study acoustic emission (AE) signals characteristics of pitting corrosion on carbon steel, Pitting corrosion process on carbon steel in 6% ferric chloride solution was monitored by AE technology. K-mean cluster algorithm was used to classify the monitored AE signals, in which the duration, counts, amplitude, absolute energy and peak frequency were analyzed as the AE signals characteristics, and different types AE sources were identified. The results showed that there were mainly three type AE sources during carbon steel pitting corrosion process in ferric chloride solution, and the different types AE sources could be classified by cluster analysis. The research results have some certain significance for AE monitoring of pitting corrosion on carbon steel.


2015 ◽  
Vol 50 (14) ◽  
pp. 1921-1935 ◽  
Author(s):  
Li Li ◽  
Yentl Swolfs ◽  
Ilya Straumit ◽  
Xiong Yan ◽  
Stepan V Lomov

Sign in / Sign up

Export Citation Format

Share Document