The Journal of the Acoustical Society of Korea (한국음향학회지)

The Acoustical Society of Korea (한국음향학회)
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Principal component analysis based frequency-time feature extraction for seismic wave classification

지진파 분류를 위한 주성분 기반 주파수-시간 특징 추출

  • 민정기 (고려대학교 전기전자공학부) ;
  • 김관태 (고려대학교 영상정보처리학부) ;
  • 구본화 (고려대학교 전기전자공학부) ;
  • 이지민 (기상청 지진화산연구과) ;
  • 안재광 (기상청 지진화산연구과) ;
  • 고한석 (고려대학교 전기전자공학부)
  • Received : 2019.04.01
  • Accepted : 2019.10.22
  • Published : 2019.11.30
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Abstract

Conventional feature of seismic classification focuses on strong seismic classification, while it is not suitable for classifying micro-seismic waves. We propose a feature extraction method based on histogram and Principal Component Analysis (PCA) in frequency-time space suitable for classifying seismic waves including strong, micro, and artificial seismic waves, as well as noise classification. The proposed method essentially employs histogram and PCA based features by concatenating the frequency and time information for binary classification which consist strong-micro-artificial/noise and micro/noise and micro/artificial seismic waves. Based on the recent earthquake data from 2017 to 2018, effectiveness of the proposed feature extraction method is demonstrated by comparing it with existing methods.

기존의 지진파 분류 특징은 강진에 초점이 맞추어져 있어서 미소지진과 같은 지진파는 다소 적합하지 않다. 본 연구에서는 강진과 더불어 미소지진, 인공지진, 잡음 분류에 적합한 특징 추출을 위해 주파수-시간 공간 내에서 히스토그램과 주성분 기반 특징 추출방법을 제안한다. 제안된 방법은 지진파의 주파수 관련 정보와 시간 관련 정보를 결합하는 방법을 적용한 히스토그램 기반 특징 추출방법과 주성분 기반 특징 추출방법을 이용하여 지진(강진, 미소지진, 인공지진)과 잡음, 미소지진과 잡음, 미소지진과 인공지진을 이진 분류한다. 2017년~2018년 최근 국내지진 자료와 분류 성능을 토대로 제안한 특징 추출방식의 효용성을 비교 평가한다.

Keywords

References

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