Author:
Sirait Helbert,Sebayang Kerista,Humaidi Syahrul,Sembiring Timbangen,Tarigan Kerista,Sembiring Kurnia,Rahayu Teguh,Ainun Ayun Ria,Sinambela Marzuki
Abstract
Abstract
Time-frequency analysis can provide useful information in digital signal seismic data processing and interpretation. The energy concentration of the spectrum depends on the consistency of function of the time-frequency analysis and instantaneous frequency variation digital signal. In this case, we used the digital signal seismic from selected seismometer broadband which deployed in Sumatera Island. The aim of this study to classify the waveform based on the time-frequency analysis using continuous wavelet transform (CWT). The sample data used the earthquake of 20 February 2018 in North Sumatera. The result indicated the classification between the horizontal and vertical components from the seismometer broadband is different. The classification of vertical is affected by seismic source and horizontal component affected the site effect.
Reference14 articles.
1. Time-frequency analysis of earthquake records;Huerta-Lopez,2000
2. Data Analysis and Seismogram Interpretation;Bormann,2018
3. Effects of thermal variability on broadband seismometers: Controlled experiments, observations, and implications;Doody;Bull. Seismol. Soc. Am.,2018
4. Understanding the fundamentals of proteomics;Alsagaby;Curr. Top. Pept. Protein Res.,2019
Cited by
2 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. Application of Wavelet Transform for Machine Learning Classification of Time Series;Lecture Notes in Data Engineering, Computational Intelligence, and Decision Making;2022-09-14
2. The Finger Flexion Related Feature Extraction Method Based on Wavelet Time-Frequency Analysis in ECoG Signals;The 5th International Conference on Computer Science and Application Engineering;2021-10-19