Acoustic emission signal identification of different rocks based on SE-1DCNN-BLSTM network model  

作　　者：WANG Weihua WANG Tingting 

机构地区：[1]School of Electrical Engineering&Information,Northeast Petroleum University,Daqing 163318,Heilongjiang,China [2]Key Laboratory of Networking and Intelligent Control of Heilongjiang Province,Daqing 163318,Heilongjiang,China

出　　处：《Global Geology》2024年第1期43-55,共13页世界地质（英文版）

基　　金：Supported by projects of the National Natural Science Foundation of China(Nos.52074088,52174022,51574088,51404073);Provincial Outstanding Youth Reserve Talent Project of Northeast Petroleum University(No.SJQH202002);2020 Northeast Petroleum University Western Oilfield Development Special Project(No.XBYTKT202001);Postdoctoral Research Start-Up in Heilongjiang Province(Nos.LBH-Q20074,LBH-Q21086).

摘　　要：In order to study fracture mechanism of rocks in different brittle mineral contents,this study pro-poses a method to identify the acoustic emission signal released by rock fracture under different brittle miner-al content(BMC),and then determine the content of brittle matter in rock.To understand related interference such as the noises in the acoustic emission signals released by the rock mass rupture,a 1DCNN-BLSTM network model with SE module is constructed in this study.The signal data is processed through the 1DCNN and BLSTM networks to fully extract the time-series correlation features of the signals,the non-correlated features of the local space and the weak periodicity law.Furthermore,the processed signals data is input into the fully connected layers.Finally,softmax function is used to accurately identify the acoustic emission signals released by different rocks,and then determine the content of brittle minerals contained in rocks.Through experimental comparison and analysis,1DCNN-BLSTM model embedded with SE module has good anti-noise performance,and the recognition accuracy can reach more than 90 percent,which is better than the traditional deep network models and provides a new way of thinking for rock acoustic emission re-search.

关 键 词：BRITTLENESS acoustic emission signal 1DCNN BLSTM SENet 

分 类 号：P585[天文地球—岩石学]