Journal of the Computational Structural Engineering Institute of Korea (한국전산구조공학회논문집)

Computational Structural Engineering Institute of Korea (한국전산구조공학회)
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Selection of the Number and Location of Monitoring Sensors using Artificial Neural Network based on Building Structure-System Identification

인공신경망 기반 건물 구조물 식별을 통한 모니터링센서 설치 개수 및 위치 선정

  • Kim, Bub-Ryur (Department of Architectural Engineering, Kyungil University) ;
  • Choi, Se-Woon (Department of Architectural Engineering, Daegu Catholic University)
  • 김법렬 (경일대학교 건축공학과) ;
  • 최세운 (대구가톨릭대학교 건축공학과)
  • Received : 2020.06.02
  • Accepted : 2020.06.12
  • Published : 2020.10.31
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Abstract

In this study, a method for selection of the location and number of monitoring sensors in a building structure using artificial neural networks is proposed. The acceleration-history values obtained from the installed accelerometers are defined as the input values, and the mass and stiffness values of each story in a building structure are defined as the output values. To select the installation location and number of accelerometers, several installation scenarios are assumed, artificial neural networks are obtained, and the prediction performance is compared. The installation location and number of sensors are selected based on the prediction accuracy obtained in this study. The proposed method is verified by applying it to 6- and 10-story structure examples.

본 연구에서는 인공신경망을 이용해 건물 구조물의 가속도계 설치 위치 및 개수를 선정하는 방법을 제안한다. 인공신경망의 입력층에는 층에 설치되는 가속도계로부터 얻는 가속도이력데이터가 입력되며, 출력층에는 구조물을 정의하는 각 층의 질량과 강성 값을 출력하도록 신경망을 구성한다. 가속도계의 설치 위치 및 개수를 선정하기 위해 여러 설치 시나리오를 가정하고 훈련을 통해 인공신경망을 구한다. 훈련에 사용되지 않은 예제를 이용해 예측 성능을 비교하였다. 센서 개수 및 위치에 따른 예측 성능을 비교하여 설치위치 및 개수를 선정한다. 6층과 10층 예제 적용을 통해 제안하는 방법을 검증하였다.

Keywords

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