4.6 Article

MULTIFRACTAL CHARACTERISTICS AND ACOUSTIC EMISSION OF COAL WITH JOINTS UNDER UNIAXIAL LOADING

出版社

WORLD SCIENTIFIC PUBL CO PTE LTD
DOI: 10.1142/S0218348X17500451

关键词

Multifractal Characteristics; Acoustic Emission; Initial Joints; Failure Process; Coal

资金

  1. National Key Research Development Program of China [2016YF C0801401]
  2. National natural science foundation of China [51634001, 51674254]
  3. Fundamental Research Funds for the Central Universities [2015XKZD04]
  4. Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD)

向作者/读者索取更多资源

In order to explore the causes of acoustic emission (AE) signals during coal failure, the coal samples with original joints were subjected to uniaxial compression experiments, and the AE signals were monitored by AEwin Test for Express-8.0. Based on the multifractal theory, the multifractal characteristics of AE were analyzed. The results showed that the AE counts and accumulative counts change over time corresponded well with the load-time, which reflected the degree of crack evolution and loading. During the initial loading stage, the cracks expanded gradually along the trace of the original cracks, which could induce a few AE events, while with the increase of load, the cracks enlarged gradually and then joined together to form a macroscopic fracture, which would cause much more AE events within a larger value. Multifractal spectrum [f(alpha)-alpha] of AE was more concentrated in the right side, illustrating that the frequency of small signals was greater than that of the large signals in AE sequences, which revealed cracks expanding and microfracture events dominated during the loading process. The greater the multifractal spectrum width (Delta alpha) was, the larger the AE signals differences were, which reflected that AE varied more intensely. The more developed the original cracks, the more obvious the multifractal characteristics. This research revealed the causes and percentage of the AE events within small or large signals, which would help us to recognize crack evolution of coal and generation mechanism of AE.

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