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Geomechanics and Engineering
  Volume 20, Number 2, January25 2020 , pages 113-120
DOI: https://doi.org/10.12989/gae.2020.20.2.113
 


Experimental investigation on multi-parameter classification predicting degradation model for rock failure using Bayesian method
Chunlai Wang, Changfeng Li, Zeng Chen, Zefeng Liao, Guangming Zhao, Feng Shi and Weijian Yu

 
Abstract
    Rock damage is the main cause of accidents in underground engineering. It is difficult to predict rock damage accurately by using only one parameter. In this study, a rock failure prediction model was established by using stress, energy, and damage. The prediction level was divided into three levels according to the ratio of the damage threshold stress to the peak stress. A classification predicting model was established, including the stress, energy, damage and AE impact rate using Bayesian method. Results show that the model is good practicability and effectiveness in predicting the degree of rock failure. On the basis of this, a multi-parameter classification predicting deterioration model of rock failure was established. The results provide a new idea for classifying and predicting rockburst.
 
Key Words
    rock failure; multi-parameter; acoustic emission; Bayesian; classified predicting
 
Address
Chunlai Wang, Changfeng Li, Zeng Chen, Zefeng Liao and Feng Shi: School of Energy and Mining Engineering, China University of Mining and Technology Beijing, 100083, Beijing, China

Guangming Zhao:School of Energy and Safety Engineering, Anhui University of Science and Technology, 232001, Huainan, Anhui, China

Weijian Yu: School of Resource and Environment and Safety Engineering, Hunan University of Science and Technology, 411201, Hunan Xiangtan, China
 

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