한국구조물진단유지관리공학회 논문집 (Journal of the Korea institute for structural maintenance and inspection)

  • 제19권4호
  • /
  • Pages.43-48
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  • 2015
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  • 2234-6937(pISSN)
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  • 2287-6979(eISSN)
한국구조물진단유지관리공학회 (Korea Institute for Structural Maintenance Inspection)
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지진계 저주파수 잡음의 ARMA 모델링 및 칼만필터를 이용한 지진계 동적범위 향상 방법

A Method to Enhance Dynamic Range for Seismic Sensor Using ARMA Modelling of Low Frequency Noise and Kalman Filtering

  • 투고 : 2014.12.31
  • 심사 : 2015.06.19
  • 발행 : 2015.07.30
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초록

본 연구에서는 지진계 센서의 동적범위를 향상시키는 새로운 방법을 제안하였다. 먼저, 센서에 포함된 저주파수 대역 잡음을 ARMA(Auto Regresive Moving Average) 모델로 모델링하고 시스템 식별 방법으로 그 모델을 식별한다. 다음으로, 모델링된 잡음과 지진파 입력을 칼만필터 식에 포함하여 칼만필터에 의한 지진파입력을 추정한다. 제안한 방법을 새로이 개발된 MEMS 기반 3축 가속도 형태의 지진계에 적용하여 성능을 검증하였다. 시험 결과는 제안한 방법이 단순한 LPF(Low Pass Filter)를 사용한 경우에 비해 동적범위를 개선시킴을 보여준다.

In this study, a method to enhance the dynamic range of seismic sensor is proposed. The low frequency noise included in the measurement of seismic sensor is modelled as an ARMA(Auto Regressive Moving Average) model and the order and parameters of the model are identified through system identification method. The identified noise model is augmented into Kalmman filter which estimate seismic signal from sensor measurement. The proposed method is applied to a newly developed seismic sensor which is MEMS based 3-axis accelerometer type. The experiment show that the proposed method can enhance the dynamic range compared to the simple low pass filtering.

키워드

참고문헌

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