Geomechanics and Engineering

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Cracks evolution and multifractal of acoustic emission energy during coal loading

  • Kong, Xiangguo (Key Laboratory of Gas and Fire Control for Coal Mines, China University of Mining and Technology) ;
  • Wang, Enyuan (Key Laboratory of Gas and Fire Control for Coal Mines, China University of Mining and Technology) ;
  • He, Xueqiu (School of Safety Engineering, China University of Mining and Technology) ;
  • Liu, Xiaofei (Key Laboratory of Gas and Fire Control for Coal Mines, China University of Mining and Technology) ;
  • Li, Dexing (Key Laboratory of Gas and Fire Control for Coal Mines, China University of Mining and Technology) ;
  • Liu, Quanlin (Key Laboratory of Gas and Fire Control for Coal Mines, China University of Mining and Technology)
  • Received : 2017.03.07
  • Accepted : 2017.06.27
  • Published : 2018.02.10
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Abstract

Coal samples with different joints morphology were subjected to uniaxial compression experiments, cracks evolution was recorded by Nikon D5300 and acoustic emission (AE) energy signals were collected by AEwin Test for Express-8.0. During loading process, coal samples deformed elastically with no obvious cracks changes, then they expanded gradually along the trace of the original cracks, accompanied by the formation of secondary cracks, and eventually produced a large-scale fracture. It was more interesting that the failure mode of samples were all shear shape, whatever the original cracks morphology was. With cracks and damage evolution, AE energy radiated regularly. At the early loading stage, micro damage and small scale fracture events only induced a few AE events with less energy, while large scale fracture leaded to a number of AE events with more energy at the later stage. Based on the multifractal theory, the multifractal spectrum could explain AE energy signals frequency responses and the causes of AE events with load. Multifractal spectrum width (${\Delta}{\alpha}$), could reflect the differences between the large and small AE energy signals. And another parameter (${\Delta}f$) could reflect the relationship between the frequency of the least and greatest signals in the AE energy time series. This research is helpful for us to understand cracks evolution and AE energy signals causes.

Keywords

Acknowledgement

Supported by : Central Universities

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