Open AccessFeature Extraction and Analysis of Microseismic Signal Based on Convolutional Neural Network
Author(s) -
Hui Zhang,
Huifang Zhai,
Ke Zhang,
Lujun Wang,
Xing Zhao,
Wei Jian-min
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/2143/1/012017
Subject(s) - microseism , computer science , convolutional neural network , feature extraction , feature engineering , artificial intelligence , artificial neural network , feature (linguistics) , big data , pattern recognition (psychology) , data mining , wavelet , signal (programming language) , machine learning , deep learning , engineering , linguistics , philosophy , civil engineering , programming language
Seismic detection technology has been widely used in safety detection of engineering construction abroad. Although it has just started in the field of engineering in our country, its role is becoming more and more important. Through computer technology, micro-seismic detection can provide accurate data for the construction safety detection of large-scale projects, which has important practical significance for the rapid and effective identification of micro-seismic signals. Based on this, the purpose of this article is to study the feature extraction and classification of microseismic signals based on neural games. This article first summarizes the development status of microseismic monitoring technology. Using traditional convolutional neural networks for analysis, a multi-scale feature fusion network is proposed on the basis of convolutional neural networks and big data, the multi-scale feature fusion network is used to research and analyze microseismic feature extraction and classification. This article systematically explains The principle of microseismic signal acquisition and the construction of multi-scale feature fusion network. And use big data, comparative analysis method, observation method and other research methods to study the theme of this article. Experimental research shows that the db7 wavelet base has little effect on the Megatron signal.