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A Study of the Optimal Displacement Analysis Algorithm for Retaining Wall Displacement Measurement System Based on 2D LiDAR Sensor

2D LiDAR 센서 기반 흙막이 벽체 변위 계측 시스템의 최적 변위 분석 알고리즘 연구

  • Kim, Jun-Sang (Department of Architectural Engineering, Inha University) ;
  • Lee, Gil-yong (Department of Architectural Engineering, Inha University) ;
  • Yoou, Geon hee (Department of Architectural Engineering, Inha University) ;
  • Kim, Young Suk (Department of Architectural Engineering, Inha University)
  • 김준상 (인하대학교 건축공학과) ;
  • 이길용 (인하대학교 건축공학과) ;
  • 유건희 (인하대학교 건축공학과) ;
  • 김영석 (인하대학교 건축공학과)
  • Received : 2022.11.29
  • Accepted : 2023.02.18
  • Published : 2023.03.31

Abstract

Inclinometer has several problems of 1)difficulty installing inclinometer casing, 2) measuring 2D local lateral displacement of retaining wall, 3) measurement by manpower. To solve such problems, a 2D LiDAR sensor-based retaining wall displacement measurement system was developed in previous studies. The purpose of this study is to select a displacement analysis algorithm to be applied in the retaining wall displacement measurement system. As a result of the displacement analysis algorithm selection, the M3C2 (Multiple Model to Model Cloud Comparison) algorithm with a displacement estimation error of 2mm was selected as the displacement analysis algorithm. If the M3C2 algorithm is applied in the system and the reliability of the displacement analysis result is secured through several field experiments. Convenient management of the displacement for the retaining wall is possible in comparison with the current measurement management.

선행연구에서는 지중경사계의 문제점인 1) 지중경사계관 설치의 어려움, 2) 단면 변위 파악의 한계성, 3) 인력 중심의 계측 방식을 해결하기 위한 2D LiDAR 센서 기반의 흙막이 벽체 변위 계측 시스템을 개발하였다. 본 연구의 목적은 선행연구에서 개발된 흙막이 벽체 변위 계측 시스템 내 탑재될 변위 분석 알고리즘을 선정하는 것이다. 변위 분석 알고리즘 선정 결과, 변위 추정 오차가 2mm인 M3C2 알고리즘이 흙막이 벽체 변위 분석 알고리즘으로 선정되었다. 본 연구 결과에서 선정된 M3C2 알고리즘이 흙막이 벽체 변위 계측 시스템에 탑재되고 수차례의 현장 실험을 통해 변위 분석 결과의 신뢰성이 담보될 경우 흙막이 벽체 변위 계측 시스템이 현행 계측관리 대비 변위 계측의 편리성 측면에서 효과적으로 흙막이 벽체의 변위를 관리할 수 있을 것으로 판단된다.

Keywords

Acknowledgement

이 논문은 정부(과학기술정보통신부)의 재원으로 한국연구재단의 지원을 받아 수행된 연구임(No. 2020R1A2C2008616)

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