Time-frequency analysis and identification for micro-seismic signals based on RST-NMF model
ZHANG Faquan1,2,WANG Haifei1, WANG Guofu1,2,YE Jincai1,2
1.School of Information and Communication, Guilin University of Electronic Technology, Guilin 541004, China;
2.Guangxi Provincial Key Lab of Wireless Wideband Communication & Signal Processing, Guilin 541004, China
Abstract：Aiming at the problem of micro-seismic signals being difficult to accurately identify, a time-frequency analysis and classification method based on RST-NMF model was proposed.Firstly, S-transform was performed for a micro-seismic signal to obtain a time-frequency matrix, and this matrix was rearranged in frequency direction.The non-negative matrix factor (NMF) technique was used to obtain resolved vectors in time domain and frequency one.Macro and micro statistics were extracted from these vectors to construct the signal’s feature space, and SVM was used to do classification.The test results of SAN Daogou minefield showed that the time-frequency analysis method of RST has a good clustering for frequency domain dispersed energy groups; local characteristics and internal relations of a micro-seismic signal are obtained to the greatest extent from the time-frequency matrix with the NMF technique; extracting macro and micro statistics of resolved vectors can ensure the completeness of a signal feature space and effectively avoid the occurrence of over-fitting during classification; the correct rate of classification can reach 94%.
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