scholarly journals Identifying critical failure information of thermal damaged sandstone through acoustic emission signal

2021 ◽  
Vol 18 (4) ◽  
pp. 558-566
Author(s):  
Weiqiang Zhang ◽  
Zhoujian Shi ◽  
Zuoquan Wang ◽  
Shaoteng Zhang
Keyword(s):  
Acoustic Emission ◽  
Critical Point ◽  
High Temperatures ◽  
Acoustic Emission Signal ◽  
Large Scale ◽  
B Value ◽  
Energy Curve ◽  
Cumulative Energy ◽  
Temperature Range ◽  
Emission Signal

Abstract The changes in the acoustic emission signals of sandstone after treatment at different high temperatures are examined in this study. The results show that there is a critical point on the cumulative energy curve of the acoustic emission signals (almost between 60 and 90% of the ratio of the loading time and the total loading time), which can be used to identify the failure of sandstone that has been damaged by exposure to a temperature of 900°C. As the temperature increases, the position of the critical point gradually changes, which indicates that high temperatures increase the plasticity of rock, and this gradually reduces the brittleness. The changes in b-value of acoustic emission shows that the transition behavior of rock from brittleness to plasticity is more obvious at temperatures higher than 600°C, and the large-scale micro cracking takes place at that temperature range, which is the main reason for the weakening and brittleness and the strengthening of plasticity of the sandstone.

Identifying the Crack Nature Using b-Value Acoustic Emission Signal Analysis

2019 ◽  
pp. 1065-1076
Author(s):  
N. A. A. S. Bahari ◽  
Shahiron Shahidan ◽  
M. F. M. Shukri ◽  
Sharifah Salwa Mohd Zuki ◽  
M. Y. Norbazlan ◽  
...  
Keyword(s):  
Acoustic Emission ◽  
Acoustic Emission Signal ◽  
Signal Analysis ◽  
B Value ◽  
Emission Signal

Discussion on the Relationship between Rockburst Proneness of Rock and its AE b-Value

2011 ◽  
Vol 137 ◽  
pp. 398-402
Author(s):  
Guang Zhang ◽  
Mo Xiao Li ◽  
Jing Xi Chen
Keyword(s):  
Acoustic Emission ◽  
Acoustic Emission Signal ◽  
Peak Stress ◽  
B Value ◽  
Uniaxial Compression Test ◽  
B Values ◽  
Emission Signal ◽  
Whole Process ◽  
In The Beginning ◽  
The Relationship

In order to strengthen the study on rockburst prediction and inquire the relationship between rockburst proneness of rock and its AE b-value, we select three typical rocks of volcanic, sedimentary, and metamorphic to conduct indoor rock mechanics test. Uniaxial compression test are carried to calculate the rockburst proneness of three kinds of rocks, at the meantime we collect the acoustic emission signal during the whole process by acoustic emission instrument. After analyzing the different AE features of all kinds of rocks, we find that the AE b-values of three kinds of rocks both develop in the beginning of two different loading conditions. The AE b-values of marble and sandstone change in a more stable way, and the b-value of granite decline at the 50% of the peak stress. The b-value of granite is the biggest and the sandstone’s is the smallest.

scholarly journals Identification of crack development in granite under triaxial compression based on the acoustic emission signal

2021 ◽  
Vol 17 (1) ◽  
pp. 155014772098611 ◽  
Author(s):  
Tianzuo Wang ◽  
Linxiang Wang ◽  
Fei Xue ◽  
Mengya Xue
Keyword(s):  
Acoustic Emission ◽  
Frequency Domain ◽  
Acoustic Emission Signal ◽  
Triaxial Compression ◽  
B Value ◽  
Quiet Period ◽  
Active Stage ◽  
Emission Signal ◽  
The Time Domain ◽  
Granite Samples

To explore the development mechanism of cracks in the process of rock failure, triaxial compression tests with simultaneous acoustic emission monitoring were performed on granite specimens using the MTS rock mechanics test system. The frequency-domain information of the acoustic emission signal was obtained by the fast Fourier transform. The Gutenberg–Richter law was used to calculate the acoustic emission signals and obtain the b-value dynamic curve in the loading process. Combined with the stiffness curve of granite specimens and acoustic emission signal in the time domain and frequency domain, the crack development characteristics in different stages were analyzed. The results showed that the acoustic emission signals of granite samples under triaxial compression can be divided into four stages: quiet period 1, active stage 1, quiet period 2, and active stage 2. b-value attained its maximum value in the active phase 2 when it is close to the sample loss, and then drops rapidly, which means the propagation of cracks and the formation of large cracks. The acoustic emission signal’s dominant frequency was not more than 500 kHz, mostly concentrated in the medium-frequency band (100–200 kHz), which accounted for more than 80%. The proportion of signals in each frequency band can reflect the distribution of the three kinds of cracks, while the change in low-frequency signals can reflect the breakthrough of microcracks and the formation time of macrocracks in granite samples. By fully analyzing the characteristics of acoustic emission signals in the time domain and frequency domain, the time and conditions of producing large cracks can be determined accurately and efficiently.

Research of the cold resistance of metals by indentation with registration of an acoustic emission signal

2020 ◽  
pp. 61-64
Author(s):  
Yu.G. Kabaldin ◽  
A.A. Khlybov ◽  
M.S. Anosov ◽  
D.A. Shatagin
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Acoustic Emission ◽  
Acoustic Emission Signal ◽  
Low Temperatures ◽  
Cold Resistance ◽  
Emission Signal ◽  
Impact Bending ◽  
Artificial Neural

The study of metals in impact bending and indentation is considered. A bench is developed for assessing the character of failure on the example of 45 steel at low temperatures using the classification of acoustic emission signal pulses and a trained artificial neural network. The results of fractographic studies of samples on impact bending correlate well with the results of pulse recognition in the acoustic emission signal. Keywords acoustic emission, classification, artificial neural network, low temperature, character of failure, hardness. [email protected]

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