Research on acoustic emission multi-parameter time series based prediction of gas outburst

doi:10.16265/j.cnki.issn1003-3033.2018.05.022

Abstract

Abstract: In order to accurately predict coal and gas outbursts,a method was worked out for coal and gas outburst prediction based on multi-parameter time series of AE of coal rock mass fracture was proposed.The AE event rate,energy rate,and b value of coal and rock mass were selected as observation parameters,a SW-ESN prediction model was built,and used to fit and predict the multi-parameter time series of AE in coal and rock masses.The swallowtail type mutation series method based on combination of mutation theory and fuzzy mathematics was used to built coal and gas outburst prediction models for the predicted AE sequences.The examples show that the SW-ESN had high prediction accuracy for AE time series,and the predicted results for outstanding situations are basically in accordance with the actual conditions on the site,and that the proposed method has certain validity and feasibility in predicting coal and gas outbursts.

Key words: coal and gas outburst, small world echo state network(SW-ESN), acoustic emission(AE), catastrophe theory, prediction

CLC Number:

X936

WANG Yuhong, LIU Lulu, FU Hua, XU Yaosong. Research on acoustic emission multi-parameter time series based prediction of gas outburst[J]. China Safety Science Journal, 2018, 28(5): 129-134.

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